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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Predicting Indoor Location Using WiFi Fingerprinting\n",
"## Submitted by Caroline Katba\n",
"\n",
"\n",
"Email: katba.caroline@gmail.com,\n",
"Cell: 312-952-2802,\n",
"[Website](http://katba-caroline.com/),\n",
"[Github](https://github.com/Katba-Caroline),\n",
"[LinkedIn](https://www.linkedin.com/in/caroline-katba-97216067/).\n",
"\n",
"### Notebook Table of Contents\n",
"- Capstone Project\n",
" - Exploratory Data Analysis (EDA)\n",
" - Preprocessing\n",
" - Model Applications\n",
" - Model Predictions\n",
" - Model Predictions on Validation Data \n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"# Capstone Project: Predicting indoor location using WiFi fingerprinting"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Many businesses and service providers rely on localization services in order to better serve their patrons. Thanks to the inclusion of GPS sensors in mobile devices, Outdoor localization problems have been solved in a variety of ways and very accurately. However, indoor localization is still an open problem mainly due to the loss of GPS signal in indoor environments.\n",
"Therefore, the problem of indoor localization has recently garnered increased attention from researchers who have opted to focus more on cheaper software solutions in place of expensive hardware solutions. \n",
"\n",
"Indoor localization has many use cases and exhibits great potential for solving problems in:\n",
"- Indoor navigation for humans and robots\n",
"- Targeted advertising \n",
"- Emergency response\n",
"- Assisted living \n",
"\n",
"**Data**\n",
"\n",
"This data set is still unfortunately one of a kind and was recently presented by Joaquín Torres-Sospedra, Raúl Montoliu, Adolfo Martínez-Usó, Tomar J. Arnau, Joan P. Avariento, Mauri Benedito-Bordonau, Joaquín Huerta [UJIIndoorLoc: A New Multi-building and Multi-floor Database for WLAN Fingerprint-based Indoor Localization Problems In Proceedings of the Fifth International Conference on Indoor Positioning and Indoor Navigation, 2014.](https://www.ncbi.nlm.nih.gov/pubmed/28287447)\n",
"\n",
"The UJIIndoorLoc database covers three buildings of Universitat Jaume I with 4 or more floors and almost 110.000 m2. It was created in 2013 by means of more than 20 different users and 25 Android devices. The database consists of 19,937 training/reference records (trainingData.csv file) and 1111 validation/test records (validationData.csv file).\n",
"\n",
"The 529 attributes contain the WiFi fingerprint, the coordinates where it was taken, and other useful information. Each WiFi fingerprint can be characterized by the detected Wireless Access Points (WAPs) and the corresponding Received Signal Strength Intensity (RSSI). The intensity values are represented as negative integer values ranging -104dBm (extremely poor signal) to 0dbM. The positive value 100 is used to denote when a WAP was not detected. During the database creation, 520 different WAPs were detected. Thus, the WiFi fingerprint is composed by 520 intensity values.\n",
"\n",
"**Approaches in the Literature**\n",
"\n",
"\n",
"Although available Data for indoor localization has unfortunately been scant, many have used this data to solve several problems in a variety of ways. Those approaches include the following: \n",
"\n",
"- Location identification using regression techniques\n",
"- Floor positioning using classification\n",
"- Building recognition using deep learning models\n",
"- Trajectory tracking using a combination of the above methods\n",
"- read more [here](https://www.ncbi.nlm.nih.gov/pubmed/28287447)\n",
"\n",
"**Literature on Indoor Localization**\n",
"\n",
"\n",
"Here are several of the papers available on the topic that helped me in my research:\n",
"- [WaP: Indoor localization and tracking using WiFi-Assisted Particle filter](https://www.researchgate.net/publication/286669860_WaP_Indoor_localization_and_tracking_using_WiFi-Assisted_Particle_filter)\n",
"- [Machine Learning for Indoor Localization\n",
"Using Mobile Phone-Based Sensors](https://arxiv.org/pdf/1505.06125.pdf)\n",
"- [Low-effort place recognition with WiFi\n",
"fingerprints using deep learning](https://arxiv.org/pdf/1611.02049v1.pdf)\n",
"- [Indoor Location Prediction Using Multiple Wireless Received\n",
"Signal Strengths](https://pdfs.semanticscholar.org/837a/2fd3f8012519707e23b2aee0850d457c950e.pdf)\n",
"- [Reliable indoor location prediction using conformal\n",
"prediction](http://khuong.uk/Papers/reliable_indoor_journal.pdf)\n",
"- [Indoor Localization using Place and Motion Signatures](https://pdfs.semanticscholar.org/2a24/2b0e4d4468946a51282fc6c1b728c8308f34.pdf)\n",
"\n",
"**My Approach: Multi-label Classification**\n",
"\n",
"To my knowledge, my approach is a unique approach that has not been applied to the problem before. I treat the problem as a classification problem, but with a twist that can save time, effort and precious memory. I treat this problem as a Multi-Label Classification problem, wherein my model simultaneously predicts *Building ID and Floor ID* for a given input. \n",
"Using a combination of Principal Component Analysis (PCA) and Multi-Label K Nearest Neighbor (MLKNN) algorithms, the model is able to predict the Building ID AND Floor ID simultaneously with 98.7% accuracy score and 0.003 Hamming loss. \n",
"This model can also be expanded to include Space ID as well.\n",
" \n",
"\n",
"The \"Difference between multi-class classification & multi-label classification is that in multi-class problems the classes are mutually exclusive, whereas for multi-label problems each label represents a different classification task, but the tasks are somehow related.\" read more [here.](https://towardsdatascience.com/journey-to-the-center-of-multi-label-classification-384c40229bff)\n",
"\n",
"Although many of the previosuly mentioned approaches yielded excellent results, many of them relied on predicting only one independent variable at a time regardless of the technique. For example, predicting only the building ID or the floor ID independently. In my opinion creating separate models for such a prediction task can be quite costly in terms of compute power, memory and time savings. Especially when using Neural Networks which can require great computational powers. Such losses, especially in time can be even deadly. Imagine a fire on the 4th floor of a particular building in a university. Having a model that can accurately and quickly predict how many people are in that exact area can be tremendously helpful to emergency response personnel.\n",
"\n",
"\n",
"\n",
"**Literature on Multi-Label Classification**\n",
"\n",
"- [How Is a Data-Driven Approach Better than Random Choice in Label Space Division for Multi-Label Classification?](https://www.mdpi.com/1099-4300/18/8/282/htm)\n",
"- [Multi-Label Classification Problem Analysis, Metrics and Techniques](https://www.springer.com/us/book/9783319411101)\n",
"- [ML-KNN: A lazy learning approach to multi-label learning](https://www.sciencedirect.com/science/article/abs/pii/S0031320307000027)\n",
"- [Multi-label Classification: Problem Transformation methods in\n",
"Tamil Phoneme classification](https://www.sciencedirect.com/science/article/pii/S1877050917319440)\n",
"- [Multi-label Classification: A Comparative Study on\n",
"Threshold Selection Methods](http://dmip.webs.upv.es/LMCE2014/Papers/lmce2014_submission_11.pdf)\n",
"- [A Tutorial on Multi-label Classification Techniques](https://www.researchgate.net/publication/225379571_A_Tutorial_on_Multi-label_Classification_Techniques)\n",
"- [Multi-Label Classification of Music Into Emotions](http://lpis.csd.auth.gr/publications/tsoumakas-ismir08.pdf)\n",
"\n",
"\n",
"**Capstone Project Table of Contents**\n",
"- Exploratory Data Analysis (EDA)\n",
"- Preprocessing\n",
"- Model Applications\n",
"- Model Predictions\n",
"- Model Predictions for Validation Data \n",
" - I tested the model on the validation data set, a completely new and unseen data set to test the model."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Capstone Project: Predicting Indoor Location Using WiFi Fingerprinting"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#necessary Libraries\n",
"import numpy as np\n",
"import pandas as pd\n",
"import time\n",
"import pprint\n",
"\n",
"#Visualizations\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from pandas.plotting import scatter_matrix\n",
"# magic word for producing visualizations in notebook\n",
"%matplotlib inline\n",
"\n",
"\n",
"#Preprocessing\n",
"from sklearn import preprocessing\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.decomposition import PCA \n",
"from scipy.sparse import lil_matrix\n",
"\n",
"#Models\n",
"from sklearn.naive_bayes import GaussianNB\n",
"from skmultilearn.problem_transform import BinaryRelevance\n",
"from skmultilearn.problem_transform import ClassifierChain\n",
"from skmultilearn.problem_transform import LabelPowerset\n",
"from skmultilearn.adapt import MLkNN\n",
"\n",
"#Scoring Metrics\n",
"from sklearn.model_selection import GridSearchCV\n",
"import sklearn.metrics as metrics\n",
"from sklearn.metrics import f1_score, fbeta_score\n",
"from sklearn.metrics import accuracy_score"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# EDA: Exploratory Data Analysis"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Load the dataset\n",
"trainingData = pd.read_csv(\"trainingData.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of columns: 529\n",
"Number of rows: 19937\n"
]
}
],
"source": [
"# Check the structure of the data after it's loaded \n",
"#(print the number of rows and columns).\n",
"num_rows, num_cols = trainingData.shape\n",
"print('Number of columns: {}'.format(num_cols))\n",
"print('Number of rows: {}'.format(num_rows))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
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"\n",
" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>WAP001</th>\n",
" <th>WAP002</th>\n",
" <th>WAP003</th>\n",
" <th>WAP004</th>\n",
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" <th>WAP009</th>\n",
" <th>WAP010</th>\n",
" <th>...</th>\n",
" <th>WAP520</th>\n",
" <th>LONGITUDE</th>\n",
" <th>LATITUDE</th>\n",
" <th>FLOOR</th>\n",
" <th>BUILDINGID</th>\n",
" <th>SPACEID</th>\n",
" <th>RELATIVEPOSITION</th>\n",
" <th>USERID</th>\n",
" <th>PHONEID</th>\n",
" <th>TIMESTAMP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>19937.000000</td>\n",
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" <td>1.993700e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>99.823644</td>\n",
" <td>99.820936</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>99.613733</td>\n",
" <td>97.130461</td>\n",
" <td>94.733661</td>\n",
" <td>93.820234</td>\n",
" <td>94.693936</td>\n",
" <td>99.163766</td>\n",
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" <td>100.0</td>\n",
" <td>-7464.275947</td>\n",
" <td>4.864871e+06</td>\n",
" <td>1.674575</td>\n",
" <td>1.212820</td>\n",
" <td>148.429954</td>\n",
" <td>1.833024</td>\n",
" <td>9.068014</td>\n",
" <td>13.021869</td>\n",
" <td>1.371421e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>5.866842</td>\n",
" <td>5.798156</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>30.305084</td>\n",
" <td>12.634045</td>\n",
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" <td>123.402010</td>\n",
" <td>6.693318e+01</td>\n",
" <td>1.223078</td>\n",
" <td>0.833139</td>\n",
" <td>58.342106</td>\n",
" <td>0.372964</td>\n",
" <td>4.988720</td>\n",
" <td>5.362410</td>\n",
" <td>5.572054e+05</td>\n",
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" <td>-97.000000</td>\n",
" <td>-90.000000</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>-97.000000</td>\n",
" <td>-98.000000</td>\n",
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" <td>-98.000000</td>\n",
" <td>-98.000000</td>\n",
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" <td>1.000000</td>\n",
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" <th>25%</th>\n",
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" <td>8.000000</td>\n",
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" <td>24.000000</td>\n",
" <td>1.371738e+09</td>\n",
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"<p>8 rows × 529 columns</p>\n",
"</div>"
],
"text/plain": [
" WAP001 WAP002 WAP003 WAP004 WAP005 \\\n",
"count 19937.000000 19937.000000 19937.0 19937.0 19937.000000 \n",
"mean 99.823644 99.820936 100.0 100.0 99.613733 \n",
"std 5.866842 5.798156 0.0 0.0 8.615657 \n",
"min -97.000000 -90.000000 100.0 100.0 -97.000000 \n",
"25% 100.000000 100.000000 100.0 100.0 100.000000 \n",
"50% 100.000000 100.000000 100.0 100.0 100.000000 \n",
"75% 100.000000 100.000000 100.0 100.0 100.000000 \n",
"max 100.000000 100.000000 100.0 100.0 100.000000 \n",
"\n",
" WAP006 WAP007 WAP008 WAP009 WAP010 \\\n",
"count 19937.000000 19937.000000 19937.000000 19937.000000 19937.000000 \n",
"mean 97.130461 94.733661 93.820234 94.693936 99.163766 \n",
"std 22.931890 30.541335 33.010404 30.305084 12.634045 \n",
"min -98.000000 -99.000000 -98.000000 -98.000000 -99.000000 \n",
"25% 100.000000 100.000000 100.000000 100.000000 100.000000 \n",
"50% 100.000000 100.000000 100.000000 100.000000 100.000000 \n",
"75% 100.000000 100.000000 100.000000 100.000000 100.000000 \n",
"max 100.000000 100.000000 100.000000 100.000000 100.000000 \n",
"\n",
" ... WAP520 LONGITUDE LATITUDE FLOOR \\\n",
"count ... 19937.0 19937.000000 1.993700e+04 19937.000000 \n",
"mean ... 100.0 -7464.275947 4.864871e+06 1.674575 \n",
"std ... 0.0 123.402010 6.693318e+01 1.223078 \n",
"min ... 100.0 -7691.338400 4.864746e+06 0.000000 \n",
"25% ... 100.0 -7594.737000 4.864821e+06 1.000000 \n",
"50% ... 100.0 -7423.060900 4.864852e+06 2.000000 \n",
"75% ... 100.0 -7359.193000 4.864930e+06 3.000000 \n",
"max ... 100.0 -7300.818990 4.865017e+06 4.000000 \n",
"\n",
" BUILDINGID SPACEID RELATIVEPOSITION USERID \\\n",
"count 19937.000000 19937.000000 19937.000000 19937.000000 \n",
"mean 1.212820 148.429954 1.833024 9.068014 \n",
"std 0.833139 58.342106 0.372964 4.988720 \n",
"min 0.000000 1.000000 1.000000 1.000000 \n",
"25% 0.000000 110.000000 2.000000 5.000000 \n",
"50% 1.000000 129.000000 2.000000 11.000000 \n",
"75% 2.000000 207.000000 2.000000 13.000000 \n",
"max 2.000000 254.000000 2.000000 18.000000 \n",
"\n",
" PHONEID TIMESTAMP \n",
"count 19937.000000 1.993700e+04 \n",
"mean 13.021869 1.371421e+09 \n",
"std 5.362410 5.572054e+05 \n",
"min 1.000000 1.369909e+09 \n",
"25% 8.000000 1.371056e+09 \n",
"50% 13.000000 1.371716e+09 \n",
"75% 14.000000 1.371721e+09 \n",
"max 24.000000 1.371738e+09 \n",
"\n",
"[8 rows x 529 columns]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#check the statistics of the data per columns\n",
"trainingData.describe()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 19937 entries, 0 to 19936\n",
"Columns: 529 entries, WAP001 to TIMESTAMP\n",
"dtypes: float64(2), int64(527)\n",
"memory usage: 80.5 MB\n"
]
}
],
"source": [
"trainingData.info()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['WAP001', 'WAP002', 'WAP003', 'WAP004', 'WAP005', 'WAP006',\n",
" 'WAP007', 'WAP008', 'WAP009', 'WAP010', 'WAP011', 'WAP012',\n",
" 'WAP013', 'WAP014', 'WAP015', 'WAP016', 'WAP017', 'WAP018',\n",
" 'WAP019', 'WAP020', 'WAP021', 'WAP022', 'WAP023', 'WAP024',\n",
" 'WAP025', 'WAP026', 'WAP027', 'WAP028', 'WAP029', 'WAP030',\n",
" 'WAP031', 'WAP032', 'WAP033', 'WAP034', 'WAP035', 'WAP036',\n",
" 'WAP037', 'WAP038', 'WAP039', 'WAP040', 'WAP041', 'WAP042',\n",
" 'WAP043', 'WAP044', 'WAP045', 'WAP046', 'WAP047', 'WAP048',\n",
" 'WAP049', 'WAP050', 'WAP051', 'WAP052', 'WAP053', 'WAP054',\n",
" 'WAP055', 'WAP056', 'WAP057', 'WAP058', 'WAP059', 'WAP060',\n",
" 'WAP061', 'WAP062', 'WAP063', 'WAP064', 'WAP065', 'WAP066',\n",
" 'WAP067', 'WAP068', 'WAP069', 'WAP070', 'WAP071', 'WAP072',\n",
" 'WAP073', 'WAP074', 'WAP075', 'WAP076', 'WAP077', 'WAP078',\n",
" 'WAP079', 'WAP080', 'WAP081', 'WAP082', 'WAP083', 'WAP084',\n",
" 'WAP085', 'WAP086', 'WAP087', 'WAP088', 'WAP089', 'WAP090',\n",
" 'WAP091', 'WAP092', 'WAP093', 'WAP094', 'WAP095', 'WAP096',\n",
" 'WAP097', 'WAP098', 'WAP099', 'WAP100', 'WAP101', 'WAP102',\n",
" 'WAP103', 'WAP104', 'WAP105', 'WAP106', 'WAP107', 'WAP108',\n",
" 'WAP109', 'WAP110', 'WAP111', 'WAP112', 'WAP113', 'WAP114',\n",
" 'WAP115', 'WAP116', 'WAP117', 'WAP118', 'WAP119', 'WAP120',\n",
" 'WAP121', 'WAP122', 'WAP123', 'WAP124', 'WAP125', 'WAP126',\n",
" 'WAP127', 'WAP128', 'WAP129', 'WAP130', 'WAP131', 'WAP132',\n",
" 'WAP133', 'WAP134', 'WAP135', 'WAP136', 'WAP137', 'WAP138',\n",
" 'WAP139', 'WAP140', 'WAP141', 'WAP142', 'WAP143', 'WAP144',\n",
" 'WAP145', 'WAP146', 'WAP147', 'WAP148', 'WAP149', 'WAP150',\n",
" 'WAP151', 'WAP152', 'WAP153', 'WAP154', 'WAP155', 'WAP156',\n",
" 'WAP157', 'WAP158', 'WAP159', 'WAP160', 'WAP161', 'WAP162',\n",
" 'WAP163', 'WAP164', 'WAP165', 'WAP166', 'WAP167', 'WAP168',\n",
" 'WAP169', 'WAP170', 'WAP171', 'WAP172', 'WAP173', 'WAP174',\n",
" 'WAP175', 'WAP176', 'WAP177', 'WAP178', 'WAP179', 'WAP180',\n",
" 'WAP181', 'WAP182', 'WAP183', 'WAP184', 'WAP185', 'WAP186',\n",
" 'WAP187', 'WAP188', 'WAP189', 'WAP190', 'WAP191', 'WAP192',\n",
" 'WAP193', 'WAP194', 'WAP195', 'WAP196', 'WAP197', 'WAP198',\n",
" 'WAP199', 'WAP200', 'WAP201', 'WAP202', 'WAP203', 'WAP204',\n",
" 'WAP205', 'WAP206', 'WAP207', 'WAP208', 'WAP209', 'WAP210',\n",
" 'WAP211', 'WAP212', 'WAP213', 'WAP214', 'WAP215', 'WAP216',\n",
" 'WAP217', 'WAP218', 'WAP219', 'WAP220', 'WAP221', 'WAP222',\n",
" 'WAP223', 'WAP224', 'WAP225', 'WAP226', 'WAP227', 'WAP228',\n",
" 'WAP229', 'WAP230', 'WAP231', 'WAP232', 'WAP233', 'WAP234',\n",
" 'WAP235', 'WAP236', 'WAP237', 'WAP238', 'WAP239', 'WAP240',\n",
" 'WAP241', 'WAP242', 'WAP243', 'WAP244', 'WAP245', 'WAP246',\n",
" 'WAP247', 'WAP248', 'WAP249', 'WAP250', 'WAP251', 'WAP252',\n",
" 'WAP253', 'WAP254', 'WAP255', 'WAP256', 'WAP257', 'WAP258',\n",
" 'WAP259', 'WAP260', 'WAP261', 'WAP262', 'WAP263', 'WAP264',\n",
" 'WAP265', 'WAP266', 'WAP267', 'WAP268', 'WAP269', 'WAP270',\n",
" 'WAP271', 'WAP272', 'WAP273', 'WAP274', 'WAP275', 'WAP276',\n",
" 'WAP277', 'WAP278', 'WAP279', 'WAP280', 'WAP281', 'WAP282',\n",
" 'WAP283', 'WAP284', 'WAP285', 'WAP286', 'WAP287', 'WAP288',\n",
" 'WAP289', 'WAP290', 'WAP291', 'WAP292', 'WAP293', 'WAP294',\n",
" 'WAP295', 'WAP296', 'WAP297', 'WAP298', 'WAP299', 'WAP300',\n",
" 'WAP301', 'WAP302', 'WAP303', 'WAP304', 'WAP305', 'WAP306',\n",
" 'WAP307', 'WAP308', 'WAP309', 'WAP310', 'WAP311', 'WAP312',\n",
" 'WAP313', 'WAP314', 'WAP315', 'WAP316', 'WAP317', 'WAP318',\n",
" 'WAP319', 'WAP320', 'WAP321', 'WAP322', 'WAP323', 'WAP324',\n",
" 'WAP325', 'WAP326', 'WAP327', 'WAP328', 'WAP329', 'WAP330',\n",
" 'WAP331', 'WAP332', 'WAP333', 'WAP334', 'WAP335', 'WAP336',\n",
" 'WAP337', 'WAP338', 'WAP339', 'WAP340', 'WAP341', 'WAP342',\n",
" 'WAP343', 'WAP344', 'WAP345', 'WAP346', 'WAP347', 'WAP348',\n",
" 'WAP349', 'WAP350', 'WAP351', 'WAP352', 'WAP353', 'WAP354',\n",
" 'WAP355', 'WAP356', 'WAP357', 'WAP358', 'WAP359', 'WAP360',\n",
" 'WAP361', 'WAP362', 'WAP363', 'WAP364', 'WAP365', 'WAP366',\n",
" 'WAP367', 'WAP368', 'WAP369', 'WAP370', 'WAP371', 'WAP372',\n",
" 'WAP373', 'WAP374', 'WAP375', 'WAP376', 'WAP377', 'WAP378',\n",
" 'WAP379', 'WAP380', 'WAP381', 'WAP382', 'WAP383', 'WAP384',\n",
" 'WAP385', 'WAP386', 'WAP387', 'WAP388', 'WAP389', 'WAP390',\n",
" 'WAP391', 'WAP392', 'WAP393', 'WAP394', 'WAP395', 'WAP396',\n",
" 'WAP397', 'WAP398', 'WAP399', 'WAP400', 'WAP401', 'WAP402',\n",
" 'WAP403', 'WAP404', 'WAP405', 'WAP406', 'WAP407', 'WAP408',\n",
" 'WAP409', 'WAP410', 'WAP411', 'WAP412', 'WAP413', 'WAP414',\n",
" 'WAP415', 'WAP416', 'WAP417', 'WAP418', 'WAP419', 'WAP420',\n",
" 'WAP421', 'WAP422', 'WAP423', 'WAP424', 'WAP425', 'WAP426',\n",
" 'WAP427', 'WAP428', 'WAP429', 'WAP430', 'WAP431', 'WAP432',\n",
" 'WAP433', 'WAP434', 'WAP435', 'WAP436', 'WAP437', 'WAP438',\n",
" 'WAP439', 'WAP440', 'WAP441', 'WAP442', 'WAP443', 'WAP444',\n",
" 'WAP445', 'WAP446', 'WAP447', 'WAP448', 'WAP449', 'WAP450',\n",
" 'WAP451', 'WAP452', 'WAP453', 'WAP454', 'WAP455', 'WAP456',\n",
" 'WAP457', 'WAP458', 'WAP459', 'WAP460', 'WAP461', 'WAP462',\n",
" 'WAP463', 'WAP464', 'WAP465', 'WAP466', 'WAP467', 'WAP468',\n",
" 'WAP469', 'WAP470', 'WAP471', 'WAP472', 'WAP473', 'WAP474',\n",
" 'WAP475', 'WAP476', 'WAP477', 'WAP478', 'WAP479', 'WAP480',\n",
" 'WAP481', 'WAP482', 'WAP483', 'WAP484', 'WAP485', 'WAP486',\n",
" 'WAP487', 'WAP488', 'WAP489', 'WAP490', 'WAP491', 'WAP492',\n",
" 'WAP493', 'WAP494', 'WAP495', 'WAP496', 'WAP497', 'WAP498',\n",
" 'WAP499', 'WAP500', 'WAP501', 'WAP502', 'WAP503', 'WAP504',\n",
" 'WAP505', 'WAP506', 'WAP507', 'WAP508', 'WAP509', 'WAP510',\n",
" 'WAP511', 'WAP512', 'WAP513', 'WAP514', 'WAP515', 'WAP516',\n",
" 'WAP517', 'WAP518', 'WAP519', 'WAP520', 'LONGITUDE', 'LATITUDE',\n",
" 'FLOOR', 'BUILDINGID', 'SPACEID', 'RELATIVEPOSITION', 'USERID',\n",
" 'PHONEID', 'TIMESTAMP'], dtype=object)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Check the columns names\n",
"col_names = trainingData.columns.values\n",
"col_names"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Percent of missing data = 0.0%\n"
]
}
],
"source": [
"#check for missing values\n",
"missing_values_count = trainingData.isnull().sum()\n",
"#uncomment this if you want to see the count of missing data per column\n",
"#missing_values_count\n",
"\n",
"# how many total missing values do we have?\n",
"total_cells = np.product(trainingData.shape)\n",
"total_missing = missing_values_count.sum()\n",
"\n",
"# percent of data that is missing\n",
"missing_percent = (total_missing/total_cells) * 100\n",
"\n",
"print('Percent of missing data = {}%'.format(missing_percent))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** This information is not quite true, we have quite a bit of information missing in the WAP Columns. However, given the sparse disrtibution of WAP data, I would like to preserve those values as they are for now, there will be more feature engineering later."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Unique Floors : [2 0 3 4 1]\n",
"Unique Buildings : [1 0 2]\n",
"Unique Space IDs : [106 103 102 122 105 101 112 104 110 108 109 111 107 15 29 117 16 28\n",
" 22 10 2 4 3 5 6 9 27 8 7 26 18 216 17 217 247 248\n",
" 246 245 244 243 242 241 240 201 202 204 203 205 207 206 209 211 208 210\n",
" 212 214 213 215 121 219 221 222 218 220 250 223 225 224 229 226 227 228\n",
" 233 231 230 232 236 235 234 237 238 239 141 140 143 113 114 116 115 120\n",
" 118 128 119 129 125 124 131 127 132 126 133 134 137 135 136 253 254 123\n",
" 130 138 139 142 146 147 249 144 1 30 25 13 12 11 14]\n",
"Unique Relative Positions : [2 1]\n",
"Unique Users : [ 2 11 3 4 5 6 7 8 9 16 10 12 13 14 15 1 17 18]\n"
]
}
],
"source": [
"#Assess unique values per building columns\n",
"unique_floors = trainingData[\"FLOOR\"].unique()\n",
"unique_bldgs = trainingData[\"BUILDINGID\"].unique()\n",
"unique_spaceid = trainingData[\"SPACEID\"].unique()\n",
"unique_rpos = trainingData[\"RELATIVEPOSITION\"].unique()\n",
"unique_users = trainingData[\"USERID\"].unique()\n",
"print('Unique Floors : {}'.format(unique_floors))\n",
"print('Unique Buildings : {}'.format(unique_bldgs))\n",
"print('Unique Space IDs : {}'.format(unique_spaceid))\n",
"print('Unique Relative Positions : {}'.format(unique_rpos))\n",
"print('Unique Users : {}'.format(unique_users))\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#Map the data i.e. see the campus\n",
"trainingData.plot(kind=\"scatter\", x=\"LONGITUDE\", y=\"LATITUDE\", alpha=0.2)\n",
"plt.savefig('data_map.png')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x504 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#map the data by user ID\n",
"#i.e. see how much of the information in each building was collected by how many users\n",
"trainingData.plot(kind=\"scatter\", x=\"LONGITUDE\", y=\"LATITUDE\", alpha=0.4, figsize=(10,7),\n",
" c=\"USERID\", cmap=plt.get_cmap(\"jet\"), colorbar=True,\n",
" sharex=False)\n",
"plt.savefig('user_map2.png')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** We can clearly see that the data in each building was collected by only a handful of the users and that not all users walked around all buildings. This can result in highly skewed data, therefore, I will choose to discard of the User ID variable. "
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x2291c610b38>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x1080 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot the correlations between the WAP features\n",
"corr_matrix = trainingData.corr()\n",
"fig = plt.figure(figsize=(15,15))\n",
"sns.heatmap(corr_matrix,xticklabels=False, yticklabels=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** While checking the correlation between WAP inputs, we can see small pockets of correlation between the data. However, most of the data is not highly correlated and will not affect our classification accuracy per se. Nevertheless, to avoid the [curse of dimentionality](https://en.wikipedia.org/wiki/Curse_of_dimensionality#Nearest_neighbor_search), I will reduce the number of features by using PCA."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1440x1080 with 9 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# plot the histograms of the attributes\n",
"trainingData.iloc[:, 520:529].hist(bins=50, figsize=(20,15))\n",
"plt.savefig(\"attribute_histogram_plots\")\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** The plots illustrate the distributions of the data. Most of the attributes have a multinomial distribution. The only variety presented in the distributions, is that of the Longitude and Latitude. Those values seem to have more a skewed normal distribution, however, those values if predicted alone cannot provide adequate information. Therefore, We would have to have the same level of confidence in a Lat regression analysis predictions as the Long regression analysis prediction to pair them together. Given this complexity, I will choose to classify the Building and Floor IDs."
]
},
{
"cell_type": "code",
"execution_count": 161,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x576 with 36 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"attributes = [\"BUILDINGID\",\"FLOOR\", \"LATITUDE\", \"LONGITUDE\", \"SPACEID\", \"RELATIVEPOSITION\"]\n",
"scatter_matrix(trainingData[attributes], figsize=(12, 8))\n",
"plt.savefig('matrix.png')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** These plots help us better understand the relationships between the potential target attributes. In this particular case, there is not much that can be inferred from these plots, except that there are no linear relationships between any of those attributes. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Preprocessing \n",
"## Preprocess the Training Data Set"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Load the dataset\n",
"trainingData = pd.read_csv(\"trainingData.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def clean_data(df):\n",
" \"\"\"\n",
" Perform feature trimming, and engineering for trainingData\n",
" Will also be applied to validationData\n",
" \n",
" INPUT: trainingData DataFrame\n",
" OUTPUT: Trimmed and cleaned trainingData DataFrame\n",
" \"\"\"\n",
" \n",
" # Reverse the representation for the values. 100=0 and teh values range from 0-105 (weakest to strongest)\n",
" #\"The intensity values are represented as negative integer values ranging -104dBm (extremely poor signal) to 0dbM.\n",
" #The positive value 100 is used to denote when a WAP was not detected.\"\n",
" df.iloc[:, 0:520] = np.where(df.iloc[:, 0:520] <= 0, \n",
" df.iloc[:, 0:520] + 105, \n",
" df.iloc[:, 0:520] - 100)\n",
" \n",
" # remove selected columns... \n",
" columns_removed = ['USERID', 'PHONEID','TIMESTAMP']\n",
" for col in columns_removed:\n",
" df.drop(col, axis=1, inplace=True)\n",
" \n",
" \n",
" # Return the cleaned dataframe.\n",
" return df \n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"#Apply Cleaning\n",
"\n",
"trainingData = clean_data(trainingData)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"def preprocess_data(df):\n",
" \"\"\"\n",
" Separates trainingData into Features and Targets\n",
" Will also be applied to validationData\n",
" \n",
" INPUT: Cleaned trainingData DataFrame\n",
" OUTPUT: trainingData as Features and Targets\n",
" \"\"\"\n",
" \n",
" global X\n",
" global y\n",
" # split the data set into features and targets(Floor and BuildingID)\n",
" X = df.drop(['LONGITUDE', 'LATITUDE','FLOOR','BUILDINGID', 'SPACEID','RELATIVEPOSITION'], axis=1)\n",
" y = df[['BUILDINGID', 'FLOOR']]\n",
" \n",
" \n",
" #create Dummies for the targets to feed into the model\n",
" y = pd.get_dummies(data=y, columns=['BUILDINGID', 'FLOOR'])\n",
" \n",
" \n",
" return X, y"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"#Apply preprocessing\n",
"\n",
"X, y = preprocess_data(trainingData)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"def split_data(preprocess_data):\n",
"# TO AVOID OVERFITTING: Split the training data into training and testing sets \n",
" global X_train\n",
" global X_test\n",
" global y_train\n",
" global y_test\n",
" \n",
" X_train, X_test, y_train, y_test = train_test_split(X, \n",
" y, \n",
" test_size = 0.2, \n",
" random_state = 42,\n",
" shuffle=True)\n",
"\n",
" # Show the results of the split\n",
" print(\"Training set has {} samples.\".format(X_train.shape[0]))\n",
" print(\"Testing set has {} samples.\".format(X_test.shape[0]))\n",
" return X_train, X_test, y_train, y_test"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Training set has 15949 samples.\n",
"Testing set has 3988 samples.\n"
]
}
],
"source": [
"#Apply split data\n",
"\n",
"X_train, X_test, y_train, y_test = split_data(preprocess_data)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** Although the WAPS that is all contained within the same scale (0-105), it is still considered a good idea to standardize the data so that the variables with larger variances don't overwhelm the PCA analysis. Additionally, standardizing is preferred to MinMax scaling when computing PCA because we are interested in the components that maximize the variance. Therefore, I standardized our WAPs data so that those features will have a mean of 0 and standard deviation of 1. Read more [here](https://scikit-learn.org/stable/auto_examples/preprocessing/plot_scaling_importance.html), and [here](https://www.quora.com/Minmaxscaler-vs-Standardscaler-Are-there-any-specific-rules-to-use-one-over-the-other-for-a-particular-application)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\Frank the Tank\\Anaconda3\\lib\\site-packages\\sklearn\\preprocessing\\data.py:625: DataConversionWarning: Data with input dtype int64 were all converted to float64 by StandardScaler.\n",
" return self.partial_fit(X, y)\n",
"C:\\Users\\Frank the Tank\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:10: DataConversionWarning: Data with input dtype int64 were all converted to float64 by StandardScaler.\n",
" # Remove the CWD from sys.path while we load stuff.\n",
"C:\\Users\\Frank the Tank\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:11: DataConversionWarning: Data with input dtype int64 were all converted to float64 by StandardScaler.\n",
" # This is added back by InteractiveShellApp.init_path()\n"
]
}
],
"source": [
"#Scale Data with Standard Scaler\n",
"\n",
"scaler = StandardScaler()\n",
"\n",
"#Fit only the training set\n",
"#this will help us transform the validation data \n",
"scaler.fit(X_train)\n",
" \n",
"# Apply transform to both the training set and the test set.\n",
"X_train = scaler.transform(X_train)\n",
"X_test = scaler.transform(X_test)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of PCA Components = 258.\n",
"Total Variance Explained by PCA Components = 0.9501844395759895.\n"
]
}
],
"source": [
"#Apply PCA while keeping 95% of the variation in the data\n",
"pca = PCA(.95)\n",
"\n",
" \n",
"#Fit only the training set \n",
"pca.fit(X_train)\n",
"\n",
"# Apply PCA transform to both the training set and the test set. \n",
"X_train_pca = pca.transform(X_train)\n",
"X_test_pca = pca.transform(X_test)\n",
"\n",
"print(\"Number of PCA Components = {}.\".format(pca.n_components_))\n",
"#print(pca.n_components_)\n",
"print(\"Total Variance Explained by PCA Components = {}.\".format(pca.explained_variance_ratio_.sum()))\n",
"#print(pca.explained_variance_ratio_.sum())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"**Comment:** After applying PCA to our data, we can see that our features have been reduced from 520 to 258. I chose 95% of the total explained variance because it seemed like a close enough representation of the total variance.\n"
]
},
{
"cell_type": "code",
"execution_count": 223,
"metadata": {},
"outputs": [
{
"data": {
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ixq/lLKN7DIN7xnPY4DRfOPO2niVGR4awctkfCm0iIiLt1LaGRtYW17BqUyUrC6t2BjX/kZrJsZEckJ7Aj8f3Y2h6AgekJzCkVwJx3fQrvrPRNyoiItIOlNVsZ3lBJcsKKlhWUMnKokrWldTsHK0ZFR7GwJ7xHDIw1RvOeidyQHoCPRO6afqMLkKhTUREpA055732bFlBJcsLKlheWMmygkoKK75rPeuTFM2w3okcO7wXQ9MTGZaeQFZaHJGd9PZMEhiFNhERkSCpb/SwtqTa14LmbUVbXlC5c0qNMIOBPeKZlJ3C8D6JjOiTxPDeiZpKQ3ZLoU1ERKQV1Dd6+HZTFd/kVbAkv4Kl+RWsLKraOXIzOjKMA9ITOXl0H0b4AtrQXgmahFYCptAmIiKylxo9jjXF1SzJK+eb/AqW5Hm7OXcEtMToCEZlJHHhIVm+gJZIVmocEerelP2g0CYiItICj8exrrSGb/LLWZJXwTd53oECtfXe6TXiu0Uwsm8iFx6Sxai+SRyYkURmSqwGB0irU2gTERHxU1hRy8KN5SzKLWdJXjlL8yup3ua9Bi06MoyRfZI4a2I/DsxIYlTfZAakxemOAdImFNpERKTLqt3eyDf5FSzcuIWFG8tZmLuFTZXbAO8UG8P6JHL62L6MykhidEYyA3uoi1NCR6FNRES6BOccOaU1O8PZwo3lrCyqotE3D1pmSiyTB6Qytl8yYzO7M6x3IlERCmjSfii0iYhIp1SzrYGFG8uZt6FsZ3dnRW094L0ObXS/JH4+dSBjM5MZ0y+Z1PhuIa5YpGUKbSIi0ikUVtQyb/0W5m/YwrwNZSwvqMTjwAyG9EzgxJHpjM30tqIN7BFPuK5Dkw5GoU1ERDqcRo9jZVGlN6D5glp+eS0AMZHhjOmXzC+OHMS4/t05qH933SRdOgWFNhERafdqtjWwKLeceeu37Ozu3DGis1diN8b3T+GSKdmMz/Jei6bbPUlnpNAmIiLtTknVNubklDF3fRnzNpSxotA7YMAMhvZK4LSxfRjfP4Vx/buT0T1Gc6JJl6DQJiIiIVdcWcdXOWV8tW4zX6/bzNqSGuC7rs4rjhjIuP7dGZvZnaQYdXVK16TQJiIiba6gvJavczbz9boyvs4pI6fUG9ISukUwPqs7Px7fj0nZKYzsm6SuThEfhTYREQkq5xx5W2q9rWg5ZXyds5ncMu+ggcToCCZmp3DOxEwmD0hlWO8ETV4r0gyFNhERaXUF5bV8vqaUL9du5qt1mymoqAOge2wkE7NTuOiQbCYNSOGA9ERNvSESIIU2ERHZbxVb6/lyXSmz15TyxZrNrPN1d6bGRTFpQAo/y05l0oAUhvRM0H06RfaRQpuIiOy1uvpG5q3fwudrS/l8TSnf5FfgHMRGhTN5QCrnTMpkyuA0hvZK0MhOkVai0CYiInvU6HEsza/wtqStLWXu+i1sb/AQEWaMzUzml0cP5tBBaYzOSNb9OkWCRKFNRER2q6iijk+/LWHWtyXMXlO6876dB6QncN7k/kwZlMaE7BTiu+lXiUhb0N80EREBYFuDt8tz1rclzFpVwqpNVYD3jgPHDe/FlMFpHDIwjR4JurG6SCgotImIdGHrS2uY9W0Jn35bwhdrN1Nb30hkuDEhK4UbDzqAqUN76Lo0kXZCoU1EpAupq2/kq3Wb+WhlMbO+LWHD5q0A9E+N5cfjM5g6pAeTB6QSpy5PkXZHfytFRDq54so6Pl5VzIcripm9ppSt2xuJjgzj0IFpXDIlm8MH9yArLS7UZYrIHii0iYh0Ms45luZX8uHKTXy0spgleRUA9EmK5ocHZXDUsJ4cPCCV6MjwEFcqIntDoU1EpBPYur2Bz9ds5iNfUNtUuQ0zGNsvmd8cP5SjDujJAem6Nk2kI1NoExHpoIqr6nhv2SY+WLGJL9ZuZnuDh/huEUwd0oOjDujJEUN7kBqvkZ4inYVCm4hIB5JbtpV3lxXxztIi5m/cgnPeQQTnTurP0cN6MiErRZPbinRSCm0iIu3cmuJq3l1WxNtLC1maXwnAsN6J/OroIZw4Kp3BPePV7SnSBSi0iYi0M845lhdW8s5Sb4va6uJqAMZmJnPjiQdwwsh0+qdqtKdIV6PQJiLSDng8joW55byztJB3lhWRW1ZLmMGk7FTOndyf40ekk54UHeoyRSSEghrazOwE4O9AOPC4c+6eJuszgaeAZN82Nzjn3gpmTSIi7YVzjkW55byxpJC3vimksKKOyHBjyqA0rjxyEMcM66WBBCKyU9BCm5mFAw8CxwJ5wFwzm+mcW+632e+BF5xzD5vZcOAtICtYNYmIhNqOOdTeWFLAG0sKyS+vJSo8jMOH9OD6Ew7gqGE9SYyODHWZItIOBbOlbSKwxjm3DsDMngdOBfxDmwMSfc+TgILdHcjM3N688bhx4/a6WBGRYHHOsaKwije/8Qa1DZu3EhFmHDY4jWuOHcKxI3opqInIHgUztPUFcv1e5wGTmmxzG/CemV0FxAHHBLEeEZE2tXpTFa8vKeSNJQWsK6khPMw4ZGAqVxwxkONHpJMcGxXqEkWkAwlmaNvd+POmLWZnA0865/5iZgcD/zWzkc45zy47ObdXY9nHjx+/Vy1zIiKtpbCilpmLCnhlYT4ri6owg0nZKVx8aDYnjkzXNWoiss+CGdrygH5+rzP4fvfnJcAJAM65L80sGkgDioNYl4hIq6qoreedpYW8urCAr3I24xyM7pfMrdOGc9Ko3vRM1KhPEdl/wQxtc4HBZpYN5ANnAec02WYjcDTwpJkNA6KBkiDWJCLSKrY1NPLxyhJeW5TPhyuL2d7gITstjl8ePZhTx/QlO03zqIlI6wpaaHPONZjZlcC7eKfz+I9zbpmZ3QHMc87NBK4FHjOzX+PtOr3QOaeuTRFplzwex5z1Zby2KJ83lxRSWddAWnwU50zM5LSxfRmdkaQ7E4hI0AR1njbfnGtvNVl2i9/z5cChwaxBRGR/rSqq4pWF+cxclE9BRR2xUeEcPyKdU8f0YcqgNCLCda9PEQk+3RFBRGQ3CitqeW1RAa/6BhSE+6bouP7EAzh2eC9io/TPp4i0Lf2rIyLis2NAwSsL8/k6pwznYEy/ZG4/ZQQnHdibNI38FJEQUmgTkS5tx4CCVxfm89Gq7wYU/OroIZw6pg9ZGlAgIu2EQpuIdDnNDSj4v0mZnDamLwdqQIGItEMKbSLSZawsquTVhQXfG1Bw2ti+HDowVQMKRKRdU2gTkU6toLyWmYt3HVBwuAYUiEgHpH+tRKTTqaqr5+1vinh5Yd7OAQVjM5O549QRnDSqt24lJSIdkkKbiHQK9Y0ePltdwssL8nl/+Sa2+Q0oOG1sH/qnakCBiHRsCm0i0mE551iaX8lLC/J4fXEBm2u20z02kjMn9OP0sX0Z0y9ZAwpEpNNQaBORDie/vJZXF+bzysJ81hRXExUextHDenL62L4cMbQnUREaUCAinY9Cm4h0CP7XqX21rgyACVndufv0UZw0qjdJsZEhrlBEJLgU2kSk3WruOrVrjh3C6WP70i8lNtQlioi0GYU2EWlXnHN8k1/BywvydZ2aiIgfhTYRaReKKup4eWEeL83PY21JDVHhYRwzvCenj81g6pAeuk5NRLo8hTYRCZm6+kbeW76JGfPzmL26BI/zXqd26WED+MGo3iTF6Do1EZEdFNpEpE0551iYW86M+d5pOqrqGuibHMOVRw7ijIMydIN2EZFmKLSJSJvY0f05Y34e60pqiI4M4wcje/OjcRlMHpBKWJiuUxMRaYlCm4gEze66PydmpXD54QM5cVQ6CdHq/hQRCZRCm4i0KnV/iogEh0KbiLSKzdXbeGlBHs/PzVX3p4hIECi0icg+83gcX63bzHNzNvLusiLqGx3j+3fn8h+q+1NEpLUptInIXiut3saM+Xk8P2cj6zdvJSkmkvMmZ3H2xH4M7pUQ6vJERDolhTYRCYjH4/hi7Wb+N2cj7y33tqpNzE7hV8cM4YSR6URHhoe6RBGRTk2hTURaVFxV52tVy2Vj2Va6x0ZywcFZnDUxk0E940NdnohIl6HQJiLf45xj7votPP3let5ZWkSDxzF5QArXHjeE40eoVU1EJBQU2kRkp5ptDby6KJ//frmBlUVVJEZHcOEhWZwzKZMBPdSqJiISSgptIsLakmr+++UGXpqfR9W2Bob3TuSeM0Zx6pi+xESpVU1EpD1QaBPpoho9jg9XbOK/X23gs9WlRIYbPxjVm/MP7s9Bmd0x07xqIiLtiUKbSBdTVVfP9Lm5PPH5evLLa0lPjObaY4dw1sRMeiR0C3V5IiLSDIU2kS4iv7yWJz/P4fk5uVRta2BiVgq/P2kYxw7vRUR4WKjLExGRPVBoE+nkluSV8/hnObz5TSEAJ45M59LDBjCmX3KIKxMRkb2h0CbSCXk8jg9WbOLx2TnMySkjvlsEFx2SxYWHZpHRPTbU5YmIyD5QaBPpRGq3NzJjQR7/mZ1DTmkNfZNj+P1JwzhzQj/dB1REpINTaBPpBIqr6nj6iw088/UGyrfWMzojiQfOHsuJI9N1vZqISCeh0CbSga0rqeaRWWt5dWEB9R4Pxw7rxaWHDWBClqbsEBHpbBTaRDqgpfkVPPzJWt5aWkhUeBg/mZDBJVMGkJ0WF+rSREQkSBTaRDqQOTllPPTJGj5ZVUJCtwgunzqQiw/N1vxqIiJdQIuhzcwygLOAw4A+QC2wFHgTeNs55wl6hSJdnHOOT74t4aGP1zB3/RZS46L4zfFDOXdyf5JiNLhARKSraDa0mdkTQF/gDeBeoBiIBoYAJwC/M7MbnHOftkWhIl1No8fx9tJCHvp4LcsLK+mTFM1t04Zz5oRM3Q9URKQLaqml7S/OuaW7Wb4UeNnMooDM4JQl0nVtb/Dw6sJ8Hp61lpzSGgb0iONPPzqQU8f0JSpCI0FFRLqqZkPb7gKbmQ0EYp1z3zjntgNrglmcSFeyvcHDi/NzeejjteSX1zKybyIP/99BHDcinfAwjQQVEenqAh6IYGY3AaMAj5l5nHPnBa8ska6jaVgbm5nMH04fydQhPTRth4iI7NTSNW1XAQ855xp9i0Y75870rVvSFsWJdGbbGhp5cV4eD328hoKKOsZmJvPHM0Zx2OA0hTUREfmellratgDvmNk/nHOvA++Z2SwgDHi3TaoT6YS2NTTywrw8HvaFtYMyk7nnhwcqrImISItauqbtGTObAfzGzC4FbgH+B0Q65yraqkCRzmJHWHvo4zUU+sLavT86kCmDFNZERGTP9nRN20BgOvAYcCfg8IY3hTaRADU0enh5YT5//2A1+eW1jOvfnfsU1kREZC+1dE3bk771McBa59xlZjYWeMzM5jjn7myjGkU6JI/H8dbSQv76/resK6lhVN8k7j5jFIerG1RERPZBSy1tY51zowHMbCGAc24hMM3MTm2L4kQ6Iuccn6wq4U/vrmJ5YSWDe8bzyLnjOH5EL4U1ERHZZy2Ftnd8Aw+igOf8VzjnXgtqVSId1FfrNvOnd1cxf8MWMlNiuf/M0Zwyuq/mWRMRkf3W0kCE680sEfA456rbsCaRDmdxbjl/fm8Vn60uJT0xmj+cPpKfjO9HZLjuYCAiIq2jpWvazgWea+6m8L67I/R2zs0OVnEi7V1u2VbufWclbywppHtsJL8/aRjnTu5PdKTuDSoiIq2rpe7RVGChmc0H5gMleG8YPwiYCpQCNwS9QpF2qKK2ngc/XsOTn68nLAyuPmoQlx0+gIToyFCXJiIinVRL3aN/N7N/AkcBhwIHArXACuA859zGtilRpP3Y3uDh2a838PcPV1NRW8+PDsrg2uOGkp4UHerSRESkk2txnjbfLaze9z1EuiznHO8u28S976wkp7SGQwelctMPhjGiT1KoSxMRkS4i4BvGi3RVi3PL+cObK5izvoxBPeN54sIJHDFUN3MXEZG2pdAm0ozCilrueXslry0qIC0+ij+cPpIzx/cjQiNCRUQkBIIa2szsBODvQDjwuHPunt1s8xPgNry3yFrsnDsnmDWJ7EldfSP/np3DPz9aQ6Nz/OLIgVw+daAGGYiISEi1NOXHNS3t6Jz7a0vrzSwceBA4FsgD5prZTOfccr9tBgOUcInFAAAgAElEQVQ3Aoc657aYWc+9KV6kNTnn+GBFMXe+sZyNZVs5YUQ6vztpGP1SYkNdmoiISIstbQm+P4cCE4CZvtfTgE8DOPZEYI1zbh2AmT0PnAos99vmMuBB59wWAOdcceCli7SeNcVV3P76cj5bXcrgnvE8c8kkpgxOC3VZIiIiO7U05cftAGb2HnCQc67K9/o24MUAjt0XyPV7nQdMarLNEN8xP8fbhXqbc+6dpgcyMxfA++00bty4vdlcurDKunr+8cFqnvxiPTFR4dxy8nDOO7i/7mQgIiLtTiDXtGUC2/1ebweyAthvd0PrmoavCGAwcASQAXxmZiOdc+UBHF9kn3k8jhkL8rjvnZVsrtnOmeP7cd3xQ0mL7xbq0kRERHYrkND2X2COmb2CN3SdDjwdwH55QD+/1xlAwW62+co5Vw/kmNkqvCFurv9Gzrm9mlth/Pjxe9UyJ13LsoIKfvfKUhbllnNQZjJPXDiRURmab01ERNq3PYY259wfzOxt4DDfoouccwsDOPZcYLCZZQP5wFlA05GhrwJnA0+aWRre7tJ1gRYvsjdqtjXwtw++5T+fr6d7bCR//cloTh/bV/OtiYhIhxDolB+xQKVz7gkz62Fm2c65nJZ2cM41mNmVwLt4r1f7j3NumZndAcxzzs30rTvOzJYDjcBvnHOb9/10RHbvg+WbuOW1pRRU1HH2xH5cf8IBJMdGhbosERGRgJlzLfckmtmtwHhgqHNuiJn1AV50zh3aFgXui/Hjx7t58+aFugxpB4oq6rht5jLeWVbEkF7x3H36KMZnpYS6LBERkZ3MbL5zbvyetgukpe10YCywAMA5V2BmCS3vIhJajR7H01+u5y/vfUt9o4ffHD+Uyw4bQFSERoWKiEjHFEho2+6cczum3TCzuCDXJLJfluZXcNMr37Akr4LDh/TgrlNHkpmqCXJFRKRjCyS0vWBmjwLJZnYZcDHwWHDLEtl7tdsb+ev7q/j37BxS4rrxj7PHMu3A3hpoICIinUIgo0f/bGbHApV4745wi3Pu/aBXJrIX5uSU8dsZi1m/eStnT8zkhhMPIClG9woVEZHOI6DRo76QpqAm7c7W7Q3c984qnvpyPRndY3ju0kkcMki3nxIRkc5nj6HNzM4A7gV64r3LgQHOOZcY5NpEWvTl2s1c/9ISNpZt5cJDsvjN8UOJ6xboLDYiIiIdSyC/4e4DpjnnVgS7GJFAVG9r4J63V/DMVxvJSo3lhZ8dzMRsTeMhIiKdWyChbZMCm7QXn68p5bczllBQUculU7K59rihxESFh7osERGRoAsktM0zs+l4bzm1bcdC59zLQatKpIna7Y3c+85KnvxiPQN6xDHj8oMZ11+tayIi0nUEEtoSga3AcX7LHKDQJm1iUW4510xfxLrSGi46NIvrTziA6Ei1romISNcSyJQfF7VFISJN1Td6eODD1Tz4yVp6JXTTyFAREenSmg1tZvZb59x9ZvYA3pa1XTjnrg5qZdKlrd5Uxa9fWMTS/Ep+eFAGt54ynMRozbsmIiJdV0stbTsGH+jO69JmPB7Hfz7P4b53V5HQLYJHzxvH8SPSQ12WiIhIyDUb2pxzr/v+fKrtypGuLLdsK9e9uJivc8o4dngv/njGKNLiu4W6LBERkXYhkMl1ewDXA8OB6B3LnXNHBbEu6WJeWZjHza8uA+DPPx7NDw/qq3uGioiI+Alk9OizwHTgJOBy4AKgJJhFSdexdXsDt7y2jBnz85iYlcJfzxxNRvfYUJclIiLS7gQS2lKdc/82s18652YBs8xsVrALk87v201V/OLZBawpqebqowZx9dGDiQgPC3VZIiIi7VIgoa3e92ehmZ0EFAAZwStJOjvnHC/My+XWmcuI7xbJM5dM4lBN5SEiItKiQELbXWaWBFwLPIB3st1fB7Uq6bSqtzXwu1e+4bVFBUwZlMb9Z46hR4IGG4iIiOxJIJPrvuF7WgEcGdxypDNbml/BVf9byIbNNVx33BB+fsQgwsM02EBERCQQLU2uu9tJdXfQ5LqyN6bP3cjNry2je2wk/7tsMpMGpIa6JBERkQ6lpZY2Taor+217g4c731jOf7/awGGD0/jbmWNI1dxrIiIie62lyXV3mVTXzBK9i11V0KuSTqGkahtXPDufueu38LPDB/Cb44dqdKiIiMg+CmRy3fHAE0CC96WVAxc75+YHuzjpuJbklfPTp+dTXrudf5w9llNG9wl1SSIiIh1aIKNH/wNc4Zz7DMDMpuANcQcGszDpuF5fXMB1Ly4mLb4bL/38EEb0SQp1SSIiIh1eIKGtakdgA3DOzTYzdZHK93g8jr998C3/+GgNE7K68/C543TvUBERkVYSSGibY2aPAv/DO5r0TOATMzsIwDm3IIj1SQexdXsD10xfzDvLivjJ+AzuOm0UURG6fk1ERKS1BBLaxvj+vLXJ8kPwhjjdOL6Ly9uylcuens+qokpuPnk4Fx+apZu9i4iItLJAJtfVhLrSrCV55Vz85Fy2NXh44qKJTB3SI9QliYiIdEp77L8ys//6bmO143V/M/swuGVJRzDr2xLO+tdXREeG88oVhyqwiYiIBFEgFx3NBr42sx+Y2WXA+8DfgluWtHevLMzjkifnkpUax8s/P4RBPeNDXZKIiEinFkj36KNmtgz4GCgFxjrnioJembRLzjke+2wdd7+1kkMGpvLoeeNIiI4MdVkiIiKdXiDdo+fhnavtfOBJ4C0zGx3kuqQd8ngcd725grvfWsnJB/bmiYsmKLCJiIi0kUBGj/4QmOKcKwb+Z2avAE/x3ahS6QLqGz1c9+JiXltUwEWHZnHzScMJC9MIURERkbYSSPfoaU1ezzGzicErSdqb7Q0ervrfAt5dtonrTziAy6cO0JQeIiIibazZ7lEze8Hv+b1NVr8RtIqkXdnW0MgVz3oD263ThvPzIwYqsImIiIRAS9e0DfZ7fmyTdZrboQvY1tDIz59ZwAcrNnHHqSO46NDsUJckIiLSZbXUPer2cZ10AnX1jVz+zHw+WVXCH04fyf9N6h/qkkRERLq0lkJbrJmNxdsaF+N7br5HTFsUJ6FRV9/IZU/PY/aaUu45YxRnTcwMdUkiIiJdXkuhrRD4q+95kd/zHa+lE6qrb+TSp+bx+dpS7v3hgfxkfL9QlyQiIiK0ENp0z9Gup77Rw5XPLWD2mlL+/OPR/GhcRqhLEhEREZ9AbmMlXUCjx3HNC4v5YEUxd542UoFNRESknVFoE5xz/O6Vb3h9cQE3nHgA503WoAMREZH2RqFN+MObK3h+bi5XHTWIy6cODHU5IiIishuB3HvUzOxcM7vF9zpTd0ToPP49O4fHZ+dw4SFZXHPskFCXIyIiIs0IpKXtIeBg4Gzf6yrgwaBVJG3mnaWF3PXmck4Ykc7NJw/XnQ5ERETasUBuGD/JOXeQmS0EcM5tMbOoINclQbZg4xZ++fwixvRL5m9njSFcN38XERFp1wJpaas3s3B8d0Ewsx6AJ6hVSVCtL63h0qfmkZ4UzePnjyc6MjzUJYmIiMgeBBLa/gG8AvQ0sz8As4G7g1qVBE1VXT0XPzUXj3M8ceEEUuO7hbokERERCcAeu0edc8+a2XzgaLy3sDrNObci6JVJq3POcd2Li9mweSvPXDKJAT3iQ12SiIiIBGiPoc3MJgPLnHMP+l4nmNkk59zXQa9OWtXDs9by7rJN/P6kYRw8MDXU5YiIiMheCKR79GGg2u91jW+ZdCCzV5fy53dXcfKBvblkSnaoyxEREZG9FEhoM+ec2/HCOechsFGn0k7kbdnKVf9bwKCe8dz7wwM1tYeIiEgHFEhoW2dmV5tZpO/xS2BdsAuT1lFX38jPn1lAQ6PjkXPHEddNeVtERKQjCiS0XQ4cAuQDecAk4KfBLEpaz62vLeOb/Ar+8pPRGnggIiLSgQUyerQYOKsNapFW9vycjUyfl8uVRw7iuBHpoS5HRERE9kMgo0d7AJcBWf7bO+cuDl5Zsr9ySmu4/fXlTBmUxq91T1EREZEOL5Du0deAJOAD4E2/xx6Z2QlmtsrM1pjZDS1s9yMzc2Y2PpDjSssaPY5rX1hEZLjx5x+P1i2qREREOoFArkqPdc5dv7cH9t366kHgWLzXws01s5nOueVNtksArgY071srefTTtSzYWM7fzhxDelJ0qMsRERGRVhBIS9sbZvaDfTj2RGCNc26dc2478Dxw6m62uxO4D6hr7kC+VriAH/tQa6exorCS+9//lh+MSufUMX1CXY6IiIi0kkBC2y/xBrdaM6s0syozqwxgv75Art/rPN+yncxsLNDPOfdGwBVLs7Y1NPLr6YtIionirtNGaT42ERGRTmSPoc05l+CcC3POxTjnEn2vEwM49u4Sw85WMDMLA+4Hrg2gBtubRwC1dUoPfLiGlUVV3HPGKFLiokJdjoiIiLSigGZaNbPuwGBg5wVSzrlP97BbHtDP73UGUOD3OgEYCXziaxFKB2aa2SnOuXmB1CXfWVlUySOz1nLGQX05ZnivUJcjIiIirSyQKT8uxdtFmgEsAiYDXwJH7WHXucBgM8vGOzHvWcA5O1Y65yqANL/3+QS4ToFt7zV6HDe89A2JMZH8/qThoS5HREREgiDQa9omABucc0cCY4GSPe3knGsArgTeBVYALzjnlpnZHWZ2yn7ULE0889UGFuWWc8vJw9UtKiIi0kkF0j1a55yrMzPMrJtzbqWZDQ3k4M65t4C3miy7pZltjwjkmLKrgvJa7ntnJYcNTtNoURERkU4skNCWZ2bJwKvA+2a2hV2vTZMQcc5xy2vLaHSOP2i0qIiISKcWyL1HT/c9vc3MPsZ7d4R3glqVBOTdZUV8sGITN/3gADJTY0NdjoiIiARRs6HNzBKdc5VmluK3+Bvfn/FAWVArkxZt3d7A7a8vZ1jvRC4+NDvU5YiIiEiQtdTS9hxwMjAf7/xq1uTPAUGvTpr1z4/WUFhRxwNnjyUiPJDxJCIiItKRNRvanHMnm/ciqanOuY1tWJPswbqSah77bB1nHNSX8Vkpe95BREREOrwWm2iccw54pY1qkQA457j99eVER4Rzw4kHhLocERERaSOB9Kt9ZWYTgl6JBOT95ZuY9W0Jvzp2CD0Tove8g4iIiHQKgUz5cSTwMzPbANTgu6bNOXdgUCuT76mrb+SON5YztFcCFxzcP9TliIiISBsKJLSdGPQqJCCPzlpH3pZanv/pZA0+EBER6WICmadtA4CZ9cTvhvHStjZV1vHIrLX8YFQ6kwekhrocERERaWN7bK4xs1PMbDWQA8wC1gNvB7kuaeIv762iwePh+hM0+EBERKQrCqSP7U5gMvCtcy4bOBr4PKhVyS6WF1Ty4vw8Ljg4i/6pcaEuR0REREIgkNBW75zbDISZWZhz7mNgTJDrEh/nHHe/tYKkmEiuOmpwqMsRERGREAlkIEK5mcUDnwLPmlkx0BDcsmSHT74tYfaaUm45eThJsZGhLkdERERCJJCWtlOBWuDXeG8UvxaYFsyixKuh0cPdb64gKzWWcydrig8REZGurKUbxv8TeM4594Xf4qeCX5LsMH1eLquLq3nk3IOIitAUHyIiIl1ZS0lgNfAXM1tvZveama5ja0NVdfXc//63TMxK4fgR6aEuR0REREKs2dDmnPu7c+5gYCpQBjxhZivM7BYzG9JmFXZRj8xaS2n1dn530jDMLNTliIiISIjtsc/NObfBOXevc24scA5wOrAi6JV1YQXltTz+WQ6njunD6H7JoS5HRERE2oFAJteNNLNpZvYs3kl1vwV+GPTKurCHP1mLxzl+c/zQUJciIiIi7URLAxGOBc4GTgLmAM8DP3XO1bRRbV3S5uptvDAvlzPGZpDRPTbU5YiIiEg70dI8bTcBzwHXOefK2qieLu+pL9azrcHDZYcPCHUpIiIi0o40G9qcc0e2ZSECNdsaeOrLDRw7vBeDesaHuhwRERFpRzT5VzsyfW4uFbX1XD51YKhLERERkXZGoa2dqG/08O/ZOUzI6s64/t1DXY6IiIi0Mwpt7cSbSwrJL69VK5uIiIjslkJbO+Cc45FZaxncM54jh/YMdTkiIiLSDim0tQOfri5lZVEVP5s6kLAw3f1AREREvk+hrR144vMceiR045TRfUJdioiIiLRTCm0hllNawyerSvi/SZlERejrEBERkd1TSgixp75YT2S4cc6kzFCXIiIiIu2YQlsIVW9rYMb8PE4a1ZueCdGhLkdERETaMYW2EHptUT7V2xo4/5CsUJciIiIi7ZxCWwi9OC+PIb3iGdsvOdSliIiISDun0BYia4qrWJRbzo/H9cNM03yIiIhIyxTaQuTF+XmEhxmnje0b6lJERESkA1BoC4GGRg8vL8jnyKE96ZHQLdTliIiISAeg0BYCn64uoaRqGz8enxHqUkRERKSDUGgLgRfn5ZESF6X7jIqIiEjAFNra2Jaa7XywYhOnjemrOyCIiIhIwJQa2thri/Kpb3TqGhUREZG9otDWxl6cn8fIvokM650Y6lJERESkA1Foa0MriypZVlDJj8f1C3UpIiIi0sEotLWht5YUEmZw0oG9Q12KiIiIdDAKbW3o7aVFTMxOIS1ec7OJiIjI3lFoayNriqtZXVzNiSPVyiYiIiJ7T6GtjbyztBCA40ekh7gSERER6YgU2trI20uLOCgzmfSk6FCXIiIiIh2QQlsbyC3byrKCSnWNioiIyD5TaGsD7y/fBKhrVERERPadQlsb+GDFJgb3jCczNTbUpYiIiEgHpdAWZJV19czJKeOY4b1CXYqIiIh0YAptQTZrVQkNHscxw3qGuhQRERHpwBTaguzDFZtIiYtiTL/uoS5FREREOjCFtiBqaPTw8aoSjhzak/AwC3U5IiIi0oEptAXRwtxyKmrrOVpdoyIiIrKfghrazOwEM1tlZmvM7IbdrL/GzJab2RIz+9DM+geznrb22bclhBkcOigt1KWIiIhIBxe00GZm4cCDwInAcOBsMxveZLOFwHjn3IHADOC+YNUTCp+tKeXAjGSSYiJDXYqIiIh0cMFsaZsIrHHOrXPObQeeB07138A597Fzbqvv5VdAxu4OZGZubx5BPKeAVdTWszi3nMMGq5VNRERE9l8wQ1tfINfvdZ5vWXMuAd4OYj1t6su1m/E4mKKuUREREWkFwQxtuxsuudtWMDM7FxgP/Gl3651ztjePVjyHfTZ7TQmxUeGMzdRUHyIiIrL/IoJ47Dygn9/rDKCg6UZmdgzwO2Cqc25bEOtpU7NXlzJ5QCpRERqgKyIiIvsvmIliLjDYzLLNLAo4C5jpv4GZjQUeBU5xzhUHsZY2lbdlK+s3b1XXqIiIiLSaoIU251wDcCXwLrACeME5t8zM7jCzU3yb/QmIB140s0VmNrOZw3Uoc3LKADh4YGqIKxEREZHOIpjdozjn3gLearLsFr/nxwTz/UNlTk4ZidERDO2VEOpSREREpJPQBVdBMGd9GROyUgjTratERESklSi0tbKSqm2sK6lhQnZKqEsRERGRTkShrZXNW++9nm2iQpuIiIi0IoW2VvZ1ThnRkWGM7JMU6lJERESkE1Foa2Vz15dxUGZ3zc8mIiIirUrJohVV1tWzvLCSCVnqGhUREZHWpdDWihZtLMc5FNpERESk1Sm0taIFG7dgBqP76Xo2ERERaV0Kba1owcZyhvZKICE6MtSliIiISCej0NZKPB7Hwo1bGJuZHOpSREREpBNSaGsl60qrqaprYGxm91CXIiIiIp2QQlsrWbChHICDFNpEREQkCBTaWsmCjVtIiolkQFpcqEsRERGRTkihrZUs8F3PppvEi4iISDAotLWCqrp6VhdXq2tUREREgkahrRUsL6jEORiVofnZREREJDgU2lrBsoJKAEb0SQxxJSIiItJZKbS1guWFlaTFd6NnQnSoSxEREZFOSqGtFSwrqFQrm4iIiASVQtt+2t7gYU1xFcMV2kRERCSIFNr207ebqqhvdGppExERkaBSaNtPy32DEIb3VmgTERGR4FFo20/LCyuJjQonK1V3QhAREZHgUWjbT8sKKhjWO1F3QhAREZGgUmjbDx6PY0Vhla5nExERkaBTaNsPhZV1VG9rYGh6QqhLERERkU5OoW0/5JTUAJCdpuvZREREJLi6dGh7/vnnGTZsGHFxcQwcOJDPPvusxe2POuoozIyGhgYAcjbXsH3TOn593qkkJSWRkZHBHXfcsXP73NxcJk+eTEpKCtdee+0uxzrhhBOYN29e65+UiIiIdEpdNrS9//77XH/99TzxxBNUVVXx6aefMmDAgGa3f/bZZ3eGtR1ySmrY/MafOPqIqZSVlTFr1iwefvhhZs6cCcAf//hHLrjgAnJycnj11Vd3hrTp06czYMAAxo8fH7wTFBERkU6ly4a2W2+9lVtuuYXJkycTFhZG37596du37263raio4Pbbb+e+++7bZfn6zTU0VBRz7rnnEh4ezsCBA5kyZQrLli0DICcnh6OOOoqkpCQmTJjAunXrqKys5J577uHuu+8O+jmKiIhI59ElQ1tjYyPz5s2jpKSEQYMGkZGRwZVXXkltbe1ut7/pppv4+c9/Tnp6+i7Lc0prGH3COTz99NPU19ezatUqvvzyS4455hgARo4cyfvvv095eTnz5s1j+PDh3HzzzfzqV78iOTk56OcpIiIinUeXDG2bNm2ivr6eGTNm8Nlnn7Fo0SIWLlzIXXfd9b1t582bx+eff85VV121y/L6Rg+5ZVuZfMSxzJgxg5iYGA444AAuueQSJkyYAMCNN97IZ599xtSpU/nFL35BfX09S5YsYdq0aZxzzjkcfvjh/POf/2yTcxYREZGOrUuGtpiYGACuuuoqevfuTVpaGtdccw1vvfXWLtt5PB6uuOIK/v73vxMREbHLurwttWyrqeTJW37KLbfcQl1dHbm5ubz77rs89NBDAKSkpDB9+nQWL17ML3/5S6666ioeeOAB7rnnHkaOHMkHH3zAI488wvLly9vmxEVERKTD6pKhrXv37mRkZGDW8l0MKisrmTdvHmeeeSbp6ek7W9AyMjKY+c6HNJQXEREezvnnn09ERAQZGRmcddZZ3wt/AP/617+YPHkyI0eO5JtvvmH8+PFERUUxatQoli5dGpTzFBERkc6jS4Y2gIsuuogHHniA4uJitmzZwt/+9jdOPvnkXbZJSkqioKCARYsWsWjRop1hbP78+cT0HUpkSl/M4LnnnsPj8VBUVMT06dMZPXr0LscpLi7mwQcf5LbbbgMgOzubjz/+mOrqaubNm9fiqFURERER6MKh7eabb2bChAkMGTKEYcOGkZ2dzZ/+9CdOP/104uPj2bhxI2ZGeno66enprFixgquvvhqAQw89lNyKepKSEnn5pZe4//77iYmJoV+/fnz99dffe6+LL76Y8vJysrKyuP/++7nxxhv56KOPyMjIoLq6ml69erX16YuIiEgH02VDW2RkJA899BDl5eUUFRVRVFTEhAkTiIuLo7q6mszMzF22j4uL44orruDRRx8FvNN9ZKfFcfTRRzN37lz+9a9/MXPmTKZNm0ZkZOQu+3o8Hv71r3+xePFi7rrrLiIjI/n666+58cYb+fWvf02/fv3a7LxFRESkY4rY8yad3/PPP09ycjKHHHIIa9as2e02EydOZOLEiXzwwQcArCupYXxW953rL7jgAsA7CW9TO+Zr69atG4MHD2bjxo1s376dl156ic8//zwIZyQiIiKdjTnnQl1Dqxs/frwL9BZRlZWVjB8/fuecanV1dWRnZ/Pb3/6WSy+99HvbP/bYY1x99dVstyg8tZU0/fwiIyMxM6KiogCora0lOzub+++/n169ejFlyhTi4uJITU3l8ccf54gjjgC8t7W66667dJcEERGRLsbM5jvn9hgAumz36A4333wzl1xyCXfeeSe/+MUv6N+/P9XV1fz0pz9l6NChvP3227tsHxERQWxsLFHpgwCIj48nPj6ebt26kZCQwJlnnslNN93EPffcw5AhQ/B4PGRkZPDwww9z0kknce6553LnnXeSk5PDtGn/397dR0dZ3Qkc//5mJpnMTBIiqahhiSmBtYIi7y9arXtqF0hrQ1fKy+5xi7RkZdtd7e6eXdh6SuzboUd33brWnm2Btrau4FJBz+IpliptdaWAQORFQGqCIFJTSBrMhCST+e0f88w4mWRCEpKZzOT3OeeeZ+Z5vfM8uTO/3Ps8995JeXk5119/ParK9OnTbUxSY4wxxnRrWAdtBw4cYMeOHXz5y19m4sSJuFwu/H4/69evx+v1cvbsWSoqKpg4cWIseBszZgwFBQWM/MS9ADz22GO0tLQQDoe5ePEimzZtoq6ujpKSklit2rFjx9i5cyctLS3MnDmT6upqbrjhBkpKSqirq+PNN99kz549rF+/nrFjxzJu3DimTp3KhQsX0nl6jDHGGDOEDOugbefOndTV1VFaWsrVV1/NQw89xMGDB6moqKCoqIidO3dSVFTE6dOnY8Hb7t27u+xn1qxZuN3uWNcdzzzzDLt27eL111/H5XIxcuRIKisrCYVCrFy5kqamJk6dOkVtbS1XXXUV8+fPp6GhgaqqKlwuF6tXr2bVqlUUFBRYzZsxxhhjgGF+T1swGKSpqSn2/uGHH6a2tpZly5ZRU1PDokWLmDBhAitXrmTdunW0trbG7mHzjZtFy4nf8sMf/pBvfetbnD9/nieeeIL777+fd955h2AwGNvvqFGj+P73v09jYyP33HNPl/vg3G43HR0d5Obm0tbWRk5ODvn5+dx8882Ulpby1ltv8Y1vfIMHHnjA7nszxhhjskxv72kb1kFbourqak6cOMFPf/pT7rzzTrZt28aKFSuYNWsWVVVVdHR0dNkmEAjQ3NyMiHQJxgByc3NxuVxcvHgxNi86EoOq4nK5CIfDQGSkhoaGBgA+9f7fSqwAABAzSURBVKlPsW3btk4PNtx444288sorzJs3j+rqau677z42b95sXYYYY4wxGcyCtstoUgyHw4wbN45wOMyRI0f49Kc/TXl5OX6/n0cffZSPf/zj/Orw27SdOcaUKVPYv38/RUVFNDY2dgrCokpKSnj33XdxuVyoapflUdF9dMftdhMOh/H7/QB0dHSQl5cHRJ5YPXr0KPPnz2fz5s2sWLHCauSMMcaYDGFPj/bBe++9x8aNG3n//fcJhULMmzePkydPsnbtWpYvX05ubi6PPPIIW7dupby8nKlTp+IORPpoC4fDFBcXM2XKFAoKCigpKYl1rhsIBAA4c+YMEAm0EjvejZcsYItuq6o0NzfT3NzMxYsXaWxspLGxkfr6eoqLi9m9ezelpaVs376dGTNmICJJk9frJRAIEAgEyMnJoaioiGuuuYZTp06xYsUKtmzZYvfTGWOMMUOI1bQB9fX1LFy4kJqaGoLBIB6Ph7Vr17J//36OHj1KTU0Nd9xxB0eOHGHSpEls2bKl0/Y+n49FixZx4sQJ9u3bR0tLC36/v9N9bYny8vI6NZlmqmhTb0FBAcFgkMLCQi5cuBALCF999VUqKyvZsWNHrCbQmnONMcaYD1jzaD9qiE6ePElZWRler5eOjg7C4TBer5fp06fT3t7O3r17WbBgAddddx3/8ewuAJoPv8jfrlxJc3MzZ8+eZfv27Z3uWYsX3/zZXTOqMekWCARoa2uL/VORn59PQUEBL730EkuXLuWpp55i6dKlFnwbY8wA6m3QhqpmXZo2bZpejrq6OgXU6/Wqx+NRl8ulfr9fKysrdeHChZqTk6P+627RwjmLNae4VP1+v7pcLgW0vLxcy8vLdcaMGTpq1Cj1eDw6evRoBdTv9yugkyZNUkABLS0tVUA9Hk+n6UCnQCDQ6b3b7R6U4wzlFL1G0SQi3b6PrhedJq5nyZIlS5aGdyosLFSPx6MjRoxQj8ejV155pZaVlenbb7+tU6ZMiU2bmpp6FXcAe3sT36Q9wBqMdLlBW1Q0eMvNzVW/3x8L4CoqKtQ3frYibvX96Rz9yle+oq5AkUIkGIr/sb/iiit07ty5nS52bm5uLGi66aabOi0rKioakD+oxADlclM0cEkM9qLHycnJUfgg6EwW6KQyALJgy5IlS5Ys9SeJiLpcrthvutvt1tzcXM3Pz1ev16sFBQXq8/m0sLBQfT6f3nXXXRoIBLSqqko3bdqk9957r27atKnX8Qa9DNrsQYQeXHvttagqq1evJhgMEgqFCIfDPP/887S8uQu0g5bjr1JbW0s42ERlZSV5eXmICDk5OXg8HhoaGnj55ZeZPXt2bL9tbW2x7kNqamo6HbO9vX1A8j7QTa/qNPUmdnsSPU4036FQqNP6yfaTCqk81lDh8/kua3uPx9NpGm3qT4doHhKlM0/GmOwW//0SDodjtzK53W7y8/MJhUIEAgHa29vx+Xy0tbXh8/k4d+4cXq+X48ePU1ZWRm1tLYsWLRr4DPYmssu0NFA1bcmsWbOmxwh9yZIl6nK5tKqqSm+99VbNzc2NLfP5fDp27Fi97bbb+hX9D1TzqdVCWcrUlKwZO11TS5aGerLv+8s/d/GtSi6XS8ePH68ejyc23bx5s+bk5OihQ4d0zpw5euzYsT7FFfSyps0eROinslXbYq+X5e3hwQcfvOQ2S5Ys4emnn+bGG2/k6NGjtLa29vp40dESoqMn9FVi578ejydWK5bpknVsnK79GGOMyU7R3wmXy4XL9UFjpcvlIj8/n0AgQCgUYvTo0YgIgUCA6upqPvaxj11qv9ZPW6pUV1dz7b/8L6raabpmzZpO623cuJFwOExNTU2fAjaINKlC1+bJ3koMRvoasCVrqhoKBirQyuaAze12D/oxrNnSGJNtot9rLpcLr9cbm4oIhYWFeDweCgsLYwFcfX09oVCItrY2Tp48yYYNG7j77rsH7PfFgrZBlCyY600VaHw6d+4clZWV+Hw+fD4fubm5+Hy+LvcfDWZglS21cj2JBjbRQppNQYjX6wWIjaIR/x8ifPBZE+9l68s5SFXQO5T/gTDZWX7M8BX9XlNV2tvbO02bm5vp6OjoMnW5XBw/fjxW09be3k59ff2A5MeCtjSJNq8mTrszcuRItm7dSjAYJBgM0traSjAY7PIHFJ0OVBA43ERrMeMLabaIdvQc7dA58UGV6GdNfJBkKJ6D4fAPRCYbyn87xlxKfM0aEBvFyOPxEA6Hyc/PJxwOM2LECEKhEMXFxZ2mY8aMobm5mZKSklj/ra2trRQXFw9I/gb111lE5gHfAdzAOlVdm7DcCzwBTAPOAYtVtW4w8zTUla3aRt3aT3aaJlO39pP9OkY0CDSZ7fz58yxfvpwXXngBiASdbreb9vZ2QqFQVt23aIwxqRD9ZyOxZ4TotKmpCZ/PR1NTEwUFBdTX18emhYWFNDQ0kJeXF5vOnTuXxx9/fMBuURm0oE1E3MB3gU8Ap4E9IvKcqh6JW+3zQIOqjhORJcC3gcWDlads01NA1xf9Df5MelnwbYwxw8tg1rTNBE6o6lsAIrIRqATig7ZKoNp5vRl4TERErV49pfoT/CXWBg70tD/5McYYY7LZYAZto4FTce9PA7OSraOqIRH5I1AM/CF+JaeflF6bNm1anzNrMttA1Tr2ZKgFqqlgn9k+s31m+8zxU5Neg9ZPm4h8Fpirql9w3t8NzFTVv4tb57Czzmnn/e+cdc4l7KuvmfwDcPJy8m+MMcYYkyLXquqVl1ppMGvaTgNj4t7/CXAmyTqnRcQDjADOJ+5IVe3ZcWOMMcYMa4PZ5cceYLyIfFhEcoElwHMJ6zwHfM55vRB40e5nM8YYY4zpatBq2px71L4EbCfS5ccGVT0sIl8jMsbWc8B64CcicoJIDduSwcqPMcYYY0wmy8qxR40xxhhjso2NiGCMMcYYkwEsaDPGGGOMyQAWtPWDiMwTkWMickJEVqU7P8ONiNSJyEEROSAie515I0XkFyLypjO9It35zDYiskFE3hORQ3Hzuj3vEvGoU0ZeF5Gp6ct59klyLapF5B2nXBwQkYq4Zauda3FMROamJ9fZR0TGiMhLIvKGiBwWkfuc+VYuUqiH65B1ZcKCtj6KG55rPjABWCoiE9Kbq2Hpz1R1sqpOd96vAn6pquOBXzrvzcD6ETAvYV6y8z4fGO+kKuB7KcrjcPEjul4LgEeccjFZVZ8HcL6flgATnW0ed77HzOULAf+oqtcDs4EvOufbykVqJbsOkGVlwoK2vosNz6WqbUB0eC6TXpXAj53XPwYWpDEvWUlVf03XfhSTnfdK4AmN2AUUicg1qclp9ktyLZKpBDaqaquq1gIniHyPmcukqu+q6j7n9QXgDSIj/Vi5SKEerkMyGVsmLGjru+6G5+rpj8MMPAVeEJHXRKTKmXeVqr4LkQIMjEpb7oaXZOfdykl6fMlpdtsQd4uAXYsUEJEyYArwW6xcpE3CdYAsKxMWtPVdd6MzWL8pqXWLqk4l0tTwRRG5Ld0ZMl1YOUm97wHlwGTgXeDfnPl2LQaZiOQDPwPuV9WmnlbtZp5diwHSzXXIujJhQVvf9WZ4LjOIVPWMM30P2EKkWvv30WYGZ/pe+nI4rCQ771ZOUkxVf6+qHaoaBn7AB809di0GkYjkEAkUnlTVZ5zZVi5SrLvrkI1lwoK2vuvN8FxmkIhIQEQKoq+BPwcO0XlItM8Bz6Ynh8NOsvP+HPDXztNys4E/RpuLzOBIuDfqM0TKBUSuxRIR8YrIh4ncBL871fnLRiIiREb2eUNV/z1ukZWLFEp2HbKxTAzmgPFZKdnwXGnO1nByFbAlUkbxAP+tqj8XkT3A0yLyeeBt4LNpzGNWEpGngNuBD4nIaWANsJbuz/vzQAWRG3yDwD0pz3AWS3ItbheRyUSaeeqAvwFwhg98GjhC5Cm7L6pqRzrynYVuAe4GDorIAWfev2LlItWSXYel2VYmbBgrY4wxxpgMYM2jxhhjjDEZwII2Y4wxxpgMYEGbMcYYY0wGsKDNGGOMMSYDWNBmjDHGGJMBLGgzxgwqEekQkQMickhE/kdE/EnWe15Eivqx/xIR2XwZ+asTkQ91Mz9fRP5LRH4nIodF5NciMqu/xxkKRGSyiFSkOx/GmP6xoM0YM9haVHWyqt4AtAH3xi90Ohp1qWqFqjb2deeqekZVFw5UZuOsIzIo+3hVnQgsA7oEdxlmMpF+wowxGciCNmNMKv0GGCciZSLyhog8DuwDxkRrvOKW/cCp4XpBRHwAIjJORHaISI2I7BORcmf9Q87yZSLyrIj8XESOicia6IFFZKuIvObss6qnTIpIOTALeMAZAgdVfUtVtznL/8GpOTwkIvc788pE5KiIrHPmPykid4jIKyLypojMdNarFpGfiMiLzvwVznwRkYecbQ+KyGJn/u0islNENjv7f9LpAR4RmSYiv3I+13b5YOiknSLybRHZLSLHReRWiYzg8jVgsVPzuXiArqkxJkUsaDPGpISIeID5wEFn1nXAE6o6RVVPJqw+HviuU8PVCNzlzH/SmX8TcDORQaATzQT+ikit0mdFZLozf7mqTgOmA38vIsU9ZHcicKC7XtJFZBqRnuxnAbOBFSIyxVk8DvgOMAn4CPCXwEeBfyLSQ3vUJOCTwBzgqyJSAvyFk+ebgDuAh+KG4ZkC3A9MAMYCt0hkrMX/BBY6n2sD8M24Y3hUdaaz3RpVbQO+Cmxyaj439fD5jTFDkA1jZYwZbL64oWV+Q2SMwBLgpKruSrJNrapGt3kNKJPImLOjVXULgKpeBHAqneL9QlXPOcueIRI07SUSqH3GWWcMkcDwXD8+z0eBLaraHHeMW4mMZ1irqged+YeBX6qqishBoCxuH8+qagvQIiIvEQk0Pwo85QSKvxeRXwEzgCZgt6qedvZ7wNlXI3AD8AvnHLjpHMRGBy9/LeHYxpgMZUGbMWawtajq5PgZTpDR3MM2rXGvOwAf0CU6SyJxbD4VkduJ1F7NUdWgiOwE8nrYx2HgJudeu3DCsp7yEZ/vcNz7MJ2/b7vksQ/77XD2JcBhVZ1ziW2i6xtjMpw1jxpjMoKqNgGnRWQBgIh4kzyJ+gkRGencB7cAeAUYATQ4AdtHiDRr9nSs3xGpnXsw7v6x8SJSCfwaWCAifhEJAJ8hUoPYF5Uikuc00d4O7HH2u1hE3CJyJXAbsLuHfRwDrhSROU7+ckRk4iWOewEo6GNejTFDhAVtxphMcjeRZs7Xgf8Dru5mnZeBnwAHgJ+p6l7g54DH2e7rQLJm2XhfcPZ/wmne/AFwRlX3AT8iElD9Flinqvv7+Dl2A9ucfHxdVc8AW4DXgRrgReCfVfVssh0496gtBL4tIjXO5735Esd9CZhgDyIYk5lENbGW3hhjMpOILAOmq+qX0p2XZESkGnhfVR9Od16MMZnFatqMMcYYYzKA1bQZY4wxxmQAq2kzxhhjjMkAFrQZY4wxxmQAC9qMMcYYYzKABW3GGGOMMRnAgjZjjDHGmAxgQZsxxhhjTAb4f+nUNGMZBcOZAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 720x432 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"def pca_plot(pca):\n",
" '''\n",
" Creates a scree plot associated with the principal components \n",
" \n",
" INPUT: pca - the result of instantian of PCA in scikit learn\n",
" \n",
" OUTPUT:\n",
" None\n",
" '''\n",
" num_components = len(pca.explained_variance_ratio_)\n",
" ind = np.arange(num_components)\n",
" vals = pca.explained_variance_ratio_\n",
" \n",
" plt.figure(figsize=(10, 6))\n",
" ax = plt.subplot(111)\n",
" cumvals = np.cumsum(vals)\n",
" ax.bar(ind, vals)\n",
" ax.plot(ind, cumvals)\n",
" for i in range(num_components):\n",
" ax.annotate(r\"%s%%\" % ((str(vals[i]*100)[:4])), (ind[i]+0.2, vals[i]), va=\"bottom\", ha=\"center\", fontsize=12)\n",
" \n",
" ax.xaxis.set_tick_params(width=0)\n",
" ax.yaxis.set_tick_params(width=2, length=12)\n",
" \n",
" ax.set_xlabel(\"Principal Component\")\n",
" ax.set_ylabel(\"Variance Explained (%)\")\n",
" plt.title('Explained Variance Per Principal Component')\n",
"\n",
"pca_plot(pca)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"**Comment:** Now that we have standardized our data and applied PCA to it, we must prepare the data for multilabel classification. It is recommended that the data be transformed into sparse matrices. Read more [here](http://scikit.ml/concepts.html)\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"#Create sparse matrices to run the scikit multilearn algorithms\n",
"\n",
"X_train_pca = lil_matrix(X_train_pca).toarray()\n",
"y_train = lil_matrix(y_train).toarray()\n",
"X_test_pca = lil_matrix(X_test_pca).toarray()\n",
"y_test = lil_matrix(y_test).toarray()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Model Applications\n",
"\n",
"When solving multi-label classification problems, there are two approaches, a traditional one and an adaptive one.\n",
"\n",
"- The traditional approach focuses on *problem transformation*. This approach transforms the multi-label classification problem into multiple single-label classification problems. Some of the algorithms include OneVsRest, Binary Relevance, Classifier Chains and Label Powerset.\n",
"\n",
"- The algorithmic adaptive approach focuses on adapting the algorithm to the multi-label classification problem directly. \n",
"\n",
"In the following section, I applied both approaches to the problem to test for better performance and therefore better explanatory power.\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Problem Transformation\n",
"### 1. Binary Relevance\n",
"\"Transforms a multi-label classification problem with L labels into L single-label separate binary classification problems using the same base classifier provided in the constructor. The prediction output is the union of all per label classifiers\" Read more [here](http://scikit.ml/api/skmultilearn.problem_transform.br.html#skmultilearn.problem_transform.BinaryRelevance)\n",
"\n",
"\"This approach is popular because it is easy to implement, however it also ignores the possible correlations between class labels.\" Read more [here](https://towardsdatascience.com/journey-to-the-center-of-multi-label-classification-384c40229bff)"
]
},
{
"cell_type": "code",
"execution_count": 225,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy = 0.1216148445336008\n",
"--- Run time: 0.08 mins ---\n"
]
}
],
"source": [
"# using binary relevance\n",
"# initialize binary relevance multi-label classifier\n",
"# with a gaussian naive bayes base classifier\n",
"start_time = time.time()\n",
"\n",
"BR_classifier = BinaryRelevance(GaussianNB())\n",
"# train\n",
"BR_classifier.fit(X_train, y_train)\n",
"# predict\n",
"predictions = BR_classifier.predict(X_test)\n",
"# accuracy\n",
"print(\"Accuracy = \",accuracy_score(y_test,predictions))\n",
"\n",
"print(\"--- Run time: %s mins ---\" % np.round(((time.time() - start_time)/60),2))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2. Classifier Chains\n",
"\"Constructs a bayesian conditioned chain of per label classifiers. This class provides implementation of Jesse Read’s problem transformation method called Classifier Chains. For L labels it trains L classifiers ordered in a chain according to the Bayesian chain rule. The first classifier is trained just on the input space, and then each next classifier is trained on the input space and all previous classifiers in the chain.\" Read more [here](http://scikit.ml/api/skmultilearn.problem_transform.cc.html#skmultilearn.problem_transform.ClassifierChain)\n",
"\n",
"\"The total number of classifiers needed for this approach is equal to the number of classes, but the training of the classifiers is more involved\" Read more [here](https://towardsdatascience.com/journey-to-the-center-of-multi-label-classification-384c40229bff)"
]
},
{
"cell_type": "code",
"execution_count": 226,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test accuracy is 0.40722166499498497\n",
"--- Run time: 0.09 mins ---\n"
]
}
],
"source": [
"# initialize classifier chains multi-label classifier\n",
"# with a gaussian naive bayes base classifier\n",
"start_time = time.time()\n",
"\n",
"CC_classifier = ClassifierChain(GaussianNB())\n",
"\n",
"# train\n",
"CC_classifier.fit(X_train, y_train)\n",
"\n",
"# predict\n",
"predictions = CC_classifier.predict(X_test)\n",
"\n",
"accuracy_score(y_test,predictions)\n",
"print('Test accuracy is {}'.format(accuracy_score(y_test, predictions)))\n",
"\n",
"print(\"--- Run time: %s mins ---\" % np.round(((time.time() - start_time)/60),2))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 3. Label Powerset\n",
"\"Transform multi-label problem to a multi-class problem. Label Powerset is a problem transformation approach to multi-label classification that transforms a multi-label problem to a multi-class problem with 1 multi-class classifier trained on all unique label combinations found in the training data. The method maps each combination to a unique combination id number, and performs multi-class classification using the classifier as multi-class classifier and combination ids as classes.\" Read more [here](http://scikit.ml/api/skmultilearn.problem_transform.lp.html#skmultilearn.problem_transform.LabelPowerset)\n",
"\n",
"\"This approach does take possible correlations between class labels into account. More commonly this approach is called the label-powerset method, because it considers each member of the power set of labels in the training set as a single label. However when the number of classes increases the number of distinct label combinations can grow exponentially. This easily leads to combinatorial explosion and thus computational infeasibility. \" Read more [here](https://towardsdatascience.com/journey-to-the-center-of-multi-label-classification-384c40229bff)"
]
},
{
"cell_type": "code",
"execution_count": 227,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Test accuracy is 0.525827482447342\n",
"--- Run time: 0.03 mins ---\n"
]
}
],
"source": [
"# initialize Label Powerset multi-label classifier\n",
"# with a gaussian naive bayes base classifier\n",
"start_time = time.time()\n",
"\n",
"LP_classifier = LabelPowerset(GaussianNB())\n",
"\n",
"# train\n",
"LP_classifier.fit(X_train, y_train)\n",
"\n",
"# predict\n",
"predictions = LP_classifier.predict(X_test)\n",
"\n",
"accuracy_score(y_test,predictions)\n",
"print('Test accuracy is {}'.format(accuracy_score(y_test, predictions)))\n",
"\n",
"print(\"--- Run time: %s mins ---\" % np.round(((time.time() - start_time)/60),2))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Adaptive Algorithms\n",
"### Multi-Label K-Nearest Neighbors (ML-KNN)\n",
"\"MLkNN builds uses k-NearestNeighbors find nearest examples to a test class and uses Bayesian inference to select assigned labels.\" Read more [here](http://scikit.ml/api/skmultilearn.adapt.mlknn.html#multilabel-k-nearest-neighbours)\n",
"\n",
"\"In detail, for each unseen instance, its k nearest neighbors in the training set are firstly identified. After that, based on statistical information gained from the label sets of these neighboring instances, i.e. the number of neighboring instances belonging to each possible class, maximum a posteriori (MAP) principle is utilized to determine the label set for the unseen instance.\" Read more [here](https://www.semanticscholar.org/paper/ML-KNN%3A-A-lazy-learning-approach-to-multi-label-Zhang-Zhou/572b7f31aee095262057fe17b181ac262eb94995)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy = 0.9839518555667001\n",
"--- Run time: 1.73 mins ---\n"
]
}
],
"source": [
"start_time = time.time()\n",
"\n",
"MLKNN_classifier = MLkNN(k=3)\n",
"\n",
"# train\n",
"MLKNN_classifier.fit(X_train_pca, y_train)\n",
"\n",
"# predict mlknn =3\n",
"predictions = MLKNN_classifier.predict(X_test_pca)\n",
"\n",
"# accuracy\n",
"print(\"Accuracy = \",accuracy_score(y_test,predictions))\n",
"\n",
"print(\"--- Run time: %s mins ---\" % np.round(((time.time() - start_time)/60),2))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** This model MLKNN is clearly the best model we have so far, the explanatory power is surging at 98% accuracy score. Timing wise, it is not as fast as the other problem transformation models, however, MLKNN is the best at prediction power. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## HyperParameter Tuning\n",
"Given that we have selected MLKNN classifier to solve our problem, I will run a grid search to find the most optimal parameters for our model. **Caution** This operation takes quite some time because it will build a model for each parameter combination possible."
]
},
{
"cell_type": "code",
"execution_count": 248,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'k': 1, 's': 0.5} 0.987710828265095\n",
"--- Run time: 69.99 mins ---\n"
]
}
],
"source": [
"#This is takes a long time to run\n",
"#Find the optimal set of parameters\n",
"\n",
"start_time = time.time()\n",
"\n",
"parameters = {'k': range(1,4), 's': [0.5, 0.7, 1.0]}\n",
"\n",
"score = 'accuracy'\n",
"\n",
"\n",
"clf = GridSearchCV(MLkNN(), parameters, scoring=score, cv=5)\n",
"clf.fit(X_train_pca, y_train)\n",
"\n",
"print (clf.best_params_, clf.best_score_)\n",
"print(\"--- Run time: %s mins ---\" % np.round(((time.time() - start_time)/60),2))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** Now that we have the most optimal parameters, I will rerun the MLKNN model to fit the data with the new parameters where K=1."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy = 0.9869608826479438\n",
"--- Run time: 0.47 mins ---\n"
]
}
],
"source": [
"start_time = time.time()\n",
"\n",
"MLKNN_1_classifier = MLkNN(k=1)\n",
"\n",
"# train\n",
"MLKNN_1_classifier.fit(X_train_pca, y_train)\n",
"\n",
"#run predictions\n",
"# predict mlknn =1\n",
"predictions = MLKNN_1_classifier.predict(X_test_pca)\n",
"\n",
"# accuracy\n",
"print(\"Accuracy = \",accuracy_score(y_test,predictions))\n",
"\n",
"\n",
"print(\"--- Run time: %s mins ---\" % np.round(((time.time() - start_time)/60),2))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** Incredible results. After tuning our hyperparameters, our model yield a 98.7% accuracy results up from 98.4% where K was equal to 3. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Scoring the best model\n",
"- Hamming Loss: The Hamming loss is the fraction of labels that are incorrectly predicted.\n",
"- Accuracy Score: In multilabel classification, this function computes subset accuracy: the set of labels predicted for a sample must exactly match the corresponding set of labels in y_true.\n"
]
},
{
"cell_type": "code",
"execution_count": 250,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hamming Loss = 0.0036985957873620864\n"
]
}
],
"source": [
"#The Hamming loss is the fraction of labels that are incorrectly predicted.\n",
"print(\"Hamming Loss = \",metrics.hamming_loss(y_test, predictions))"
]
},
{
"cell_type": "code",
"execution_count": 251,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy = 0.9869608826479438\n"
]
}
],
"source": [
"#In multilabel classification, this function computes subset accuracy: the set of labels predicted for a sample must exactly match the corresponding set of labels in y_true.\n",
"print(\"Accuracy = \",metrics.accuracy_score(y_test, predictions))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Pickle Model using Joblib\n",
"\"It may be better to use joblib’s replacement of pickle (dump & load), which is more efficient on objects that carry large numpy arrays internally as is often the case for fitted scikit-learn estimators, but can only pickle to the disk and not to a string.\" Read more [here](https://scikit-learn.org/stable/modules/model_persistence.html)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['MLKNN_1_classifier.joblib']"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#pickle model first\n",
"\n",
"from joblib import dump, load\n",
"dump(MLKNN_1_classifier, 'MLKNN_1_classifier.joblib')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load Pickled Model for Prediction"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"#load pickled model\n",
"MLKNN_1_classifier = load('MLKNN_1_classifier.joblib') "
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy = 0.9869608826479438\n"
]
}
],
"source": [
"#run predictions on our test data\n",
"# predict mlknn =1\n",
"predictions = MLKNN_1_classifier.predict(X_test_pca)\n",
"\n",
"# accuracy\n",
"print(\"Accuracy = \",accuracy_score(y_test,predictions))\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Predict the data\n",
"Below you, can see all the predictions on our test data mapped to the dictionary of column names. This tanslation will aid in understanding the output values. All the output values have been saved to an external CSV file. "
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['BUILDINGID_0', 'FLOOR_3']\n"
]
}
],
"source": [
"#See the predictions and translate them\n",
"\n",
"#map the labels to their name\n",
"labels = y.columns.tolist() \n",
"lables_dict = {key: i for i, key in enumerate(labels)}\n",
"\n",
"#Turn predictions into readable list of lists\n",
"my_predictions = predictions.rows.tolist()\n",
"\n",
"#translate the values to their keys.\n",
"#Change the my_predictions[0] value to\n",
"#my_predictions[index_value] to translate insights\n",
"get_keys = [k for k, v in lables_dict.items() \n",
" if v in my_predictions[0]]\n",
"\n",
"print(get_keys)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"#Save Predictions to new CSV \n",
"test_predictions = pd.DataFrame(my_predictions, columns=['BuildingID', 'Floor']).to_csv('test_predictions.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Predict on the Validation Data\n",
"## Here we test our model on completely new data"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"validationData = pd.read_csv(\"validationData.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of PCA Components = 258.\n",
"Total Variance Explained by PCA Components = 0.9501844395759895.\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\Frank the Tank\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:10: DataConversionWarning: Data with input dtype int64 were all converted to float64 by StandardScaler.\n",
" # Remove the CWD from sys.path while we load stuff.\n"
]
}
],
"source": [
"#Prepare Data for Model\n",
"\n",
"#Clean data\n",
"validationData = clean_data(validationData)\n",
"\n",
"#preprocess\n",
"X_valid, y_valid = preprocess_data(validationData)\n",
"\n",
"#scale\n",
"X_valid = scaler.transform(X_valid)\n",
"\n",
"#pca\n",
"X_valid_pca = pca.transform(X_valid)\n",
"\n",
"print(\"Number of PCA Components = {}.\".format(pca.n_components_))\n",
"\n",
"print(\"Total Variance Explained by PCA Components = {}.\".format(pca.explained_variance_ratio_.sum()))\n",
"\n",
"#Convert to sparse matrix\n",
"X_valid_pca = lil_matrix(X_valid_pca).toarray()\n",
"y_valid = lil_matrix(y_valid).toarray()"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy = 0.8100810081008101\n"
]
}
],
"source": [
"# predict mlknn =1\n",
"valid_predictions = MLKNN_1_classifier.predict(X_valid_pca)\n",
"\n",
"# accuracy\n",
"print(\"Accuracy = \",accuracy_score(y_valid,valid_predictions))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['BUILDINGID_1', 'FLOOR_3']\n"
]
}
],
"source": [
"#Translate\n",
"\n",
"#Turn predictions into readable list of lists\n",
"my_valid_predictions = valid_predictions.rows.tolist()\n",
"\n",
"#translate the values to their keys.\n",
"#Change the my_predictions[0] value to \n",
"#my_predictions[index_value] to translate insights\n",
"get_keys = [k for k, v in lables_dict.items() \n",
" if v in my_valid_predictions[0]]\n",
"\n",
"print(get_keys)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"#Save Predictions to new CSV \n",
"valid_predictions = pd.DataFrame(my_valid_predictions, columns=['BuildingID', 'Floor']).to_csv('valid_predictions.csv')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Predicting Indoor Location Using WiFi Fingerprinting\n",
"## Submitted by Caroline Katba\n",
"\n",
"\n",
"Email: katba.caroline@gmail.com,\n",
"[Website](http://katba-caroline.com/),\n",
"[Github](https://github.com/Katba-Caroline),\n",
"[LinkedIn](https://www.linkedin.com/in/caroline-katba-97216067/).\n",
"\n",
"### Notebook Table of Contents\n",
"- Capstone Project\n",
" - Exploratory Data Analysis (EDA)\n",
" - Preprocessing\n",
" - Model Applications\n",
" - Model Predictions\n",
" - Model Predictions on Validation Data \n",
" "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"# Capstone Project: Predicting indoor location using WiFi fingerprinting"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Many businesses and service providers rely on localization services in order to better serve their patrons. Thanks to the inclusion of GPS sensors in mobile devices, Outdoor localization problems have been solved in a variety of ways and very accurately. However, indoor localization is still an open problem mainly due to the loss of GPS signal in indoor environments.\n",
"Therefore, the problem of indoor localization has recently garnered increased attention from researchers who have opted to focus more on cheaper software solutions in place of expensive hardware solutions. \n",
"\n",
"Indoor localization has many use cases and exhibits great potential for solving problems in:\n",
"- Indoor navigation for humans and robots\n",
"- Targeted advertising \n",
"- Emergency response\n",
"- Assisted living \n",
"\n",
"**Data**\n",
"\n",
"This data set is still unfortunately one of a kind and was recently presented by Joaquín Torres-Sospedra, Raúl Montoliu, Adolfo Martínez-Usó, Tomar J. Arnau, Joan P. Avariento, Mauri Benedito-Bordonau, Joaquín Huerta [UJIIndoorLoc: A New Multi-building and Multi-floor Database for WLAN Fingerprint-based Indoor Localization Problems In Proceedings of the Fifth International Conference on Indoor Positioning and Indoor Navigation, 2014.](https://www.ncbi.nlm.nih.gov/pubmed/28287447)\n",
"\n",
"The UJIIndoorLoc database covers three buildings of Universitat Jaume I with 4 or more floors and almost 110.000 m2. It was created in 2013 by means of more than 20 different users and 25 Android devices. The database consists of 19,937 training/reference records (trainingData.csv file) and 1111 validation/test records (validationData.csv file).\n",
"\n",
"The 529 attributes contain the WiFi fingerprint, the coordinates where it was taken, and other useful information. Each WiFi fingerprint can be characterized by the detected Wireless Access Points (WAPs) and the corresponding Received Signal Strength Intensity (RSSI). The intensity values are represented as negative integer values ranging -104dBm (extremely poor signal) to 0dbM. The positive value 100 is used to denote when a WAP was not detected. During the database creation, 520 different WAPs were detected. Thus, the WiFi fingerprint is composed by 520 intensity values.\n",
"\n",
"**Approaches in the Literature**\n",
"\n",
"\n",
"Although available Data for indoor localization has unfortunately been scant, many have used this data to solve several problems in a variety of ways. Those approaches include the following: \n",
"\n",
"- Location identification using regression techniques\n",
"- Floor positioning using classification\n",
"- Building recognition using deep learning models\n",
"- Trajectory tracking using a combination of the above methods\n",
"- read more [here](https://www.ncbi.nlm.nih.gov/pubmed/28287447)\n",
"\n",
"**Literature on Indoor Localization**\n",
"\n",
"\n",
"Here are several of the papers available on the topic that helped me in my research:\n",
"- [WaP: Indoor localization and tracking using WiFi-Assisted Particle filter](https://www.researchgate.net/publication/286669860_WaP_Indoor_localization_and_tracking_using_WiFi-Assisted_Particle_filter)\n",
"- [Machine Learning for Indoor Localization\n",
"Using Mobile Phone-Based Sensors](https://arxiv.org/pdf/1505.06125.pdf)\n",
"- [Low-effort place recognition with WiFi\n",
"fingerprints using deep learning](https://arxiv.org/pdf/1611.02049v1.pdf)\n",
"- [Indoor Location Prediction Using Multiple Wireless Received\n",
"Signal Strengths](https://pdfs.semanticscholar.org/837a/2fd3f8012519707e23b2aee0850d457c950e.pdf)\n",
"- [Reliable indoor location prediction using conformal\n",
"prediction](http://khuong.uk/Papers/reliable_indoor_journal.pdf)\n",
"- [Indoor Localization using Place and Motion Signatures](https://pdfs.semanticscholar.org/2a24/2b0e4d4468946a51282fc6c1b728c8308f34.pdf)\n",
"\n",
"**My Approach: Multi-label Classification**\n",
"\n",
"To my knowledge, my approach is a unique approach that has not been applied to the problem before. I treat the problem as a classification problem, but with a twist that can save time, effort and precious memory. I treat this problem as a Multi-Label Classification problem, wherein my model simultaneously predicts *Building ID and Floor ID* for a given input. \n",
"Using a combination of Principal Component Analysis (PCA) and Multi-Label K Nearest Neighbor (MLKNN) algorithms, the model is able to predict the Building ID AND Floor ID simultaneously with 98.7% accuracy score and 0.003 Hamming loss. \n",
"This model can also be expanded to include Space ID as well.\n",
" \n",
"\n",
"The \"Difference between multi-class classification & multi-label classification is that in multi-class problems the classes are mutually exclusive, whereas for multi-label problems each label represents a different classification task, but the tasks are somehow related.\" read more [here.](https://towardsdatascience.com/journey-to-the-center-of-multi-label-classification-384c40229bff)\n",
"\n",
"Although many of the previosuly mentioned approaches yielded excellent results, many of them relied on predicting only one independent variable at a time regardless of the technique. For example, predicting only the building ID or the floor ID independently. In my opinion creating separate models for such a prediction task can be quite costly in terms of compute power, memory and time savings. Especially when using Neural Networks which can require great computational powers. Such losses, especially in time can be even deadly. Imagine a fire on the 4th floor of a particular building in a university. Having a model that can accurately and quickly predict how many people are in that exact area can be tremendously helpful to emergency response personnel.\n",
"\n",
"\n",
"\n",
"**Literature on Multi-Label Classification**\n",
"\n",
"- [How Is a Data-Driven Approach Better than Random Choice in Label Space Division for Multi-Label Classification?](https://www.mdpi.com/1099-4300/18/8/282/htm)\n",
"- [Multi-Label Classification Problem Analysis, Metrics and Techniques](https://www.springer.com/us/book/9783319411101)\n",
"- [ML-KNN: A lazy learning approach to multi-label learning](https://www.sciencedirect.com/science/article/abs/pii/S0031320307000027)\n",
"- [Multi-label Classification: Problem Transformation methods in\n",
"Tamil Phoneme classification](https://www.sciencedirect.com/science/article/pii/S1877050917319440)\n",
"- [Multi-label Classification: A Comparative Study on\n",
"Threshold Selection Methods](http://dmip.webs.upv.es/LMCE2014/Papers/lmce2014_submission_11.pdf)\n",
"- [A Tutorial on Multi-label Classification Techniques](https://www.researchgate.net/publication/225379571_A_Tutorial_on_Multi-label_Classification_Techniques)\n",
"- [Multi-Label Classification of Music Into Emotions](http://lpis.csd.auth.gr/publications/tsoumakas-ismir08.pdf)\n",
"\n",
"\n",
"**Capstone Project Table of Contents**\n",
"- Exploratory Data Analysis (EDA)\n",
"- Preprocessing\n",
"- Model Applications\n",
"- Model Predictions\n",
"- Model Predictions for Validation Data \n",
" - I tested the model on the validation data set, a completely new and unseen data set to test the model."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Capstone Project: Predicting Indoor Location Using WiFi Fingerprinting"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#necessary Libraries\n",
"import numpy as np\n",
"import pandas as pd\n",
"import time\n",
"import pprint\n",
"\n",
"#Visualizations\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from pandas.plotting import scatter_matrix\n",
"# magic word for producing visualizations in notebook\n",
"%matplotlib inline\n",
"\n",
"\n",
"#Preprocessing\n",
"from sklearn import preprocessing\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.decomposition import PCA \n",
"from scipy.sparse import lil_matrix\n",
"\n",
"#Models\n",
"from sklearn.naive_bayes import GaussianNB\n",
"from skmultilearn.problem_transform import BinaryRelevance\n",
"from skmultilearn.problem_transform import ClassifierChain\n",
"from skmultilearn.problem_transform import LabelPowerset\n",
"from skmultilearn.adapt import MLkNN\n",
"\n",
"#Scoring Metrics\n",
"from sklearn.model_selection import GridSearchCV\n",
"import sklearn.metrics as metrics\n",
"from sklearn.metrics import f1_score, fbeta_score\n",
"from sklearn.metrics import accuracy_score"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# EDA: Exploratory Data Analysis"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# Load the dataset\n",
"trainingData = pd.read_csv(\"trainingData.csv\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of columns: 529\n",
"Number of rows: 19937\n"
]
}
],
"source": [
"# Check the structure of the data after it's loaded \n",
"#(print the number of rows and columns).\n",
"num_rows, num_cols = trainingData.shape\n",
"print('Number of columns: {}'.format(num_cols))\n",
"print('Number of rows: {}'.format(num_rows))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>WAP001</th>\n",
" <th>WAP002</th>\n",
" <th>WAP003</th>\n",
" <th>WAP004</th>\n",
" <th>WAP005</th>\n",
" <th>WAP006</th>\n",
" <th>WAP007</th>\n",
" <th>WAP008</th>\n",
" <th>WAP009</th>\n",
" <th>WAP010</th>\n",
" <th>...</th>\n",
" <th>WAP520</th>\n",
" <th>LONGITUDE</th>\n",
" <th>LATITUDE</th>\n",
" <th>FLOOR</th>\n",
" <th>BUILDINGID</th>\n",
" <th>SPACEID</th>\n",
" <th>RELATIVEPOSITION</th>\n",
" <th>USERID</th>\n",
" <th>PHONEID</th>\n",
" <th>TIMESTAMP</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.0</td>\n",
" <td>19937.0</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>...</td>\n",
" <td>19937.0</td>\n",
" <td>19937.000000</td>\n",
" <td>1.993700e+04</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>19937.000000</td>\n",
" <td>1.993700e+04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>99.823644</td>\n",
" <td>99.820936</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>99.613733</td>\n",
" <td>97.130461</td>\n",
" <td>94.733661</td>\n",
" <td>93.820234</td>\n",
" <td>94.693936</td>\n",
" <td>99.163766</td>\n",
" <td>...</td>\n",
" <td>100.0</td>\n",
" <td>-7464.275947</td>\n",
" <td>4.864871e+06</td>\n",
" <td>1.674575</td>\n",
" <td>1.212820</td>\n",
" <td>148.429954</td>\n",
" <td>1.833024</td>\n",
" <td>9.068014</td>\n",
" <td>13.021869</td>\n",
" <td>1.371421e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>5.866842</td>\n",
" <td>5.798156</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8.615657</td>\n",
" <td>22.931890</td>\n",
" <td>30.541335</td>\n",
" <td>33.010404</td>\n",
" <td>30.305084</td>\n",
" <td>12.634045</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>123.402010</td>\n",
" <td>6.693318e+01</td>\n",
" <td>1.223078</td>\n",
" <td>0.833139</td>\n",
" <td>58.342106</td>\n",
" <td>0.372964</td>\n",
" <td>4.988720</td>\n",
" <td>5.362410</td>\n",
" <td>5.572054e+05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>-97.000000</td>\n",
" <td>-90.000000</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>-97.000000</td>\n",
" <td>-98.000000</td>\n",
" <td>-99.000000</td>\n",
" <td>-98.000000</td>\n",
" <td>-98.000000</td>\n",
" <td>-99.000000</td>\n",
" <td>...</td>\n",
" <td>100.0</td>\n",
" <td>-7691.338400</td>\n",
" <td>4.864746e+06</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.369909e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>...</td>\n",
" <td>100.0</td>\n",
" <td>-7594.737000</td>\n",
" <td>4.864821e+06</td>\n",
" <td>1.000000</td>\n",
" <td>0.000000</td>\n",
" <td>110.000000</td>\n",
" <td>2.000000</td>\n",
" <td>5.000000</td>\n",
" <td>8.000000</td>\n",
" <td>1.371056e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>...</td>\n",
" <td>100.0</td>\n",
" <td>-7423.060900</td>\n",
" <td>4.864852e+06</td>\n",
" <td>2.000000</td>\n",
" <td>1.000000</td>\n",
" <td>129.000000</td>\n",
" <td>2.000000</td>\n",
" <td>11.000000</td>\n",
" <td>13.000000</td>\n",
" <td>1.371716e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>...</td>\n",
" <td>100.0</td>\n",
" <td>-7359.193000</td>\n",
" <td>4.864930e+06</td>\n",
" <td>3.000000</td>\n",
" <td>2.000000</td>\n",
" <td>207.000000</td>\n",
" <td>2.000000</td>\n",
" <td>13.000000</td>\n",
" <td>14.000000</td>\n",
" <td>1.371721e+09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.0</td>\n",
" <td>100.0</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>100.000000</td>\n",
" <td>...</td>\n",
" <td>100.0</td>\n",
" <td>-7300.818990</td>\n",
" <td>4.865017e+06</td>\n",
" <td>4.000000</td>\n",
" <td>2.000000</td>\n",
" <td>254.000000</td>\n",
" <td>2.000000</td>\n",
" <td>18.000000</td>\n",
" <td>24.000000</td>\n",
" <td>1.371738e+09</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>8 rows × 529 columns</p>\n",
"</div>"
],
"text/plain": [
" WAP001 WAP002 WAP003 WAP004 WAP005 \\\n",
"count 19937.000000 19937.000000 19937.0 19937.0 19937.000000 \n",
"mean 99.823644 99.820936 100.0 100.0 99.613733 \n",
"std 5.866842 5.798156 0.0 0.0 8.615657 \n",
"min -97.000000 -90.000000 100.0 100.0 -97.000000 \n",
"25% 100.000000 100.000000 100.0 100.0 100.000000 \n",
"50% 100.000000 100.000000 100.0 100.0 100.000000 \n",
"75% 100.000000 100.000000 100.0 100.0 100.000000 \n",
"max 100.000000 100.000000 100.0 100.0 100.000000 \n",
"\n",
" WAP006 WAP007 WAP008 WAP009 WAP010 \\\n",
"count 19937.000000 19937.000000 19937.000000 19937.000000 19937.000000 \n",
"mean 97.130461 94.733661 93.820234 94.693936 99.163766 \n",
"std 22.931890 30.541335 33.010404 30.305084 12.634045 \n",
"min -98.000000 -99.000000 -98.000000 -98.000000 -99.000000 \n",
"25% 100.000000 100.000000 100.000000 100.000000 100.000000 \n",
"50% 100.000000 100.000000 100.000000 100.000000 100.000000 \n",
"75% 100.000000 100.000000 100.000000 100.000000 100.000000 \n",
"max 100.000000 100.000000 100.000000 100.000000 100.000000 \n",
"\n",
" ... WAP520 LONGITUDE LATITUDE FLOOR \\\n",
"count ... 19937.0 19937.000000 1.993700e+04 19937.000000 \n",
"mean ... 100.0 -7464.275947 4.864871e+06 1.674575 \n",
"std ... 0.0 123.402010 6.693318e+01 1.223078 \n",
"min ... 100.0 -7691.338400 4.864746e+06 0.000000 \n",
"25% ... 100.0 -7594.737000 4.864821e+06 1.000000 \n",
"50% ... 100.0 -7423.060900 4.864852e+06 2.000000 \n",
"75% ... 100.0 -7359.193000 4.864930e+06 3.000000 \n",
"max ... 100.0 -7300.818990 4.865017e+06 4.000000 \n",
"\n",
" BUILDINGID SPACEID RELATIVEPOSITION USERID \\\n",
"count 19937.000000 19937.000000 19937.000000 19937.000000 \n",
"mean 1.212820 148.429954 1.833024 9.068014 \n",
"std 0.833139 58.342106 0.372964 4.988720 \n",
"min 0.000000 1.000000 1.000000 1.000000 \n",
"25% 0.000000 110.000000 2.000000 5.000000 \n",
"50% 1.000000 129.000000 2.000000 11.000000 \n",
"75% 2.000000 207.000000 2.000000 13.000000 \n",
"max 2.000000 254.000000 2.000000 18.000000 \n",
"\n",
" PHONEID TIMESTAMP \n",
"count 19937.000000 1.993700e+04 \n",
"mean 13.021869 1.371421e+09 \n",
"std 5.362410 5.572054e+05 \n",
"min 1.000000 1.369909e+09 \n",
"25% 8.000000 1.371056e+09 \n",
"50% 13.000000 1.371716e+09 \n",
"75% 14.000000 1.371721e+09 \n",
"max 24.000000 1.371738e+09 \n",
"\n",
"[8 rows x 529 columns]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#check the statistics of the data per columns\n",
"trainingData.describe()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 19937 entries, 0 to 19936\n",
"Columns: 529 entries, WAP001 to TIMESTAMP\n",
"dtypes: float64(2), int64(527)\n",
"memory usage: 80.5 MB\n"
]
}
],
"source": [
"trainingData.info()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['WAP001', 'WAP002', 'WAP003', 'WAP004', 'WAP005', 'WAP006',\n",
" 'WAP007', 'WAP008', 'WAP009', 'WAP010', 'WAP011', 'WAP012',\n",
" 'WAP013', 'WAP014', 'WAP015', 'WAP016', 'WAP017', 'WAP018',\n",
" 'WAP019', 'WAP020', 'WAP021', 'WAP022', 'WAP023', 'WAP024',\n",
" 'WAP025', 'WAP026', 'WAP027', 'WAP028', 'WAP029', 'WAP030',\n",
" 'WAP031', 'WAP032', 'WAP033', 'WAP034', 'WAP035', 'WAP036',\n",
" 'WAP037', 'WAP038', 'WAP039', 'WAP040', 'WAP041', 'WAP042',\n",
" 'WAP043', 'WAP044', 'WAP045', 'WAP046', 'WAP047', 'WAP048',\n",
" 'WAP049', 'WAP050', 'WAP051', 'WAP052', 'WAP053', 'WAP054',\n",
" 'WAP055', 'WAP056', 'WAP057', 'WAP058', 'WAP059', 'WAP060',\n",
" 'WAP061', 'WAP062', 'WAP063', 'WAP064', 'WAP065', 'WAP066',\n",
" 'WAP067', 'WAP068', 'WAP069', 'WAP070', 'WAP071', 'WAP072',\n",
" 'WAP073', 'WAP074', 'WAP075', 'WAP076', 'WAP077', 'WAP078',\n",
" 'WAP079', 'WAP080', 'WAP081', 'WAP082', 'WAP083', 'WAP084',\n",
" 'WAP085', 'WAP086', 'WAP087', 'WAP088', 'WAP089', 'WAP090',\n",
" 'WAP091', 'WAP092', 'WAP093', 'WAP094', 'WAP095', 'WAP096',\n",
" 'WAP097', 'WAP098', 'WAP099', 'WAP100', 'WAP101', 'WAP102',\n",
" 'WAP103', 'WAP104', 'WAP105', 'WAP106', 'WAP107', 'WAP108',\n",
" 'WAP109', 'WAP110', 'WAP111', 'WAP112', 'WAP113', 'WAP114',\n",
" 'WAP115', 'WAP116', 'WAP117', 'WAP118', 'WAP119', 'WAP120',\n",
" 'WAP121', 'WAP122', 'WAP123', 'WAP124', 'WAP125', 'WAP126',\n",
" 'WAP127', 'WAP128', 'WAP129', 'WAP130', 'WAP131', 'WAP132',\n",
" 'WAP133', 'WAP134', 'WAP135', 'WAP136', 'WAP137', 'WAP138',\n",
" 'WAP139', 'WAP140', 'WAP141', 'WAP142', 'WAP143', 'WAP144',\n",
" 'WAP145', 'WAP146', 'WAP147', 'WAP148', 'WAP149', 'WAP150',\n",
" 'WAP151', 'WAP152', 'WAP153', 'WAP154', 'WAP155', 'WAP156',\n",
" 'WAP157', 'WAP158', 'WAP159', 'WAP160', 'WAP161', 'WAP162',\n",
" 'WAP163', 'WAP164', 'WAP165', 'WAP166', 'WAP167', 'WAP168',\n",
" 'WAP169', 'WAP170', 'WAP171', 'WAP172', 'WAP173', 'WAP174',\n",
" 'WAP175', 'WAP176', 'WAP177', 'WAP178', 'WAP179', 'WAP180',\n",
" 'WAP181', 'WAP182', 'WAP183', 'WAP184', 'WAP185', 'WAP186',\n",
" 'WAP187', 'WAP188', 'WAP189', 'WAP190', 'WAP191', 'WAP192',\n",
" 'WAP193', 'WAP194', 'WAP195', 'WAP196', 'WAP197', 'WAP198',\n",
" 'WAP199', 'WAP200', 'WAP201', 'WAP202', 'WAP203', 'WAP204',\n",
" 'WAP205', 'WAP206', 'WAP207', 'WAP208', 'WAP209', 'WAP210',\n",
" 'WAP211', 'WAP212', 'WAP213', 'WAP214', 'WAP215', 'WAP216',\n",
" 'WAP217', 'WAP218', 'WAP219', 'WAP220', 'WAP221', 'WAP222',\n",
" 'WAP223', 'WAP224', 'WAP225', 'WAP226', 'WAP227', 'WAP228',\n",
" 'WAP229', 'WAP230', 'WAP231', 'WAP232', 'WAP233', 'WAP234',\n",
" 'WAP235', 'WAP236', 'WAP237', 'WAP238', 'WAP239', 'WAP240',\n",
" 'WAP241', 'WAP242', 'WAP243', 'WAP244', 'WAP245', 'WAP246',\n",
" 'WAP247', 'WAP248', 'WAP249', 'WAP250', 'WAP251', 'WAP252',\n",
" 'WAP253', 'WAP254', 'WAP255', 'WAP256', 'WAP257', 'WAP258',\n",
" 'WAP259', 'WAP260', 'WAP261', 'WAP262', 'WAP263', 'WAP264',\n",
" 'WAP265', 'WAP266', 'WAP267', 'WAP268', 'WAP269', 'WAP270',\n",
" 'WAP271', 'WAP272', 'WAP273', 'WAP274', 'WAP275', 'WAP276',\n",
" 'WAP277', 'WAP278', 'WAP279', 'WAP280', 'WAP281', 'WAP282',\n",
" 'WAP283', 'WAP284', 'WAP285', 'WAP286', 'WAP287', 'WAP288',\n",
" 'WAP289', 'WAP290', 'WAP291', 'WAP292', 'WAP293', 'WAP294',\n",
" 'WAP295', 'WAP296', 'WAP297', 'WAP298', 'WAP299', 'WAP300',\n",
" 'WAP301', 'WAP302', 'WAP303', 'WAP304', 'WAP305', 'WAP306',\n",
" 'WAP307', 'WAP308', 'WAP309', 'WAP310', 'WAP311', 'WAP312',\n",
" 'WAP313', 'WAP314', 'WAP315', 'WAP316', 'WAP317', 'WAP318',\n",
" 'WAP319', 'WAP320', 'WAP321', 'WAP322', 'WAP323', 'WAP324',\n",
" 'WAP325', 'WAP326', 'WAP327', 'WAP328', 'WAP329', 'WAP330',\n",
" 'WAP331', 'WAP332', 'WAP333', 'WAP334', 'WAP335', 'WAP336',\n",
" 'WAP337', 'WAP338', 'WAP339', 'WAP340', 'WAP341', 'WAP342',\n",
" 'WAP343', 'WAP344', 'WAP345', 'WAP346', 'WAP347', 'WAP348',\n",
" 'WAP349', 'WAP350', 'WAP351', 'WAP352', 'WAP353', 'WAP354',\n",
" 'WAP355', 'WAP356', 'WAP357', 'WAP358', 'WAP359', 'WAP360',\n",
" 'WAP361', 'WAP362', 'WAP363', 'WAP364', 'WAP365', 'WAP366',\n",
" 'WAP367', 'WAP368', 'WAP369', 'WAP370', 'WAP371', 'WAP372',\n",
" 'WAP373', 'WAP374', 'WAP375', 'WAP376', 'WAP377', 'WAP378',\n",
" 'WAP379', 'WAP380', 'WAP381', 'WAP382', 'WAP383', 'WAP384',\n",
" 'WAP385', 'WAP386', 'WAP387', 'WAP388', 'WAP389', 'WAP390',\n",
" 'WAP391', 'WAP392', 'WAP393', 'WAP394', 'WAP395', 'WAP396',\n",
" 'WAP397', 'WAP398', 'WAP399', 'WAP400', 'WAP401', 'WAP402',\n",
" 'WAP403', 'WAP404', 'WAP405', 'WAP406', 'WAP407', 'WAP408',\n",
" 'WAP409', 'WAP410', 'WAP411', 'WAP412', 'WAP413', 'WAP414',\n",
" 'WAP415', 'WAP416', 'WAP417', 'WAP418', 'WAP419', 'WAP420',\n",
" 'WAP421', 'WAP422', 'WAP423', 'WAP424', 'WAP425', 'WAP426',\n",
" 'WAP427', 'WAP428', 'WAP429', 'WAP430', 'WAP431', 'WAP432',\n",
" 'WAP433', 'WAP434', 'WAP435', 'WAP436', 'WAP437', 'WAP438',\n",
" 'WAP439', 'WAP440', 'WAP441', 'WAP442', 'WAP443', 'WAP444',\n",
" 'WAP445', 'WAP446', 'WAP447', 'WAP448', 'WAP449', 'WAP450',\n",
" 'WAP451', 'WAP452', 'WAP453', 'WAP454', 'WAP455', 'WAP456',\n",
" 'WAP457', 'WAP458', 'WAP459', 'WAP460', 'WAP461', 'WAP462',\n",
" 'WAP463', 'WAP464', 'WAP465', 'WAP466', 'WAP467', 'WAP468',\n",
" 'WAP469', 'WAP470', 'WAP471', 'WAP472', 'WAP473', 'WAP474',\n",
" 'WAP475', 'WAP476', 'WAP477', 'WAP478', 'WAP479', 'WAP480',\n",
" 'WAP481', 'WAP482', 'WAP483', 'WAP484', 'WAP485', 'WAP486',\n",
" 'WAP487', 'WAP488', 'WAP489', 'WAP490', 'WAP491', 'WAP492',\n",
" 'WAP493', 'WAP494', 'WAP495', 'WAP496', 'WAP497', 'WAP498',\n",
" 'WAP499', 'WAP500', 'WAP501', 'WAP502', 'WAP503', 'WAP504',\n",
" 'WAP505', 'WAP506', 'WAP507', 'WAP508', 'WAP509', 'WAP510',\n",
" 'WAP511', 'WAP512', 'WAP513', 'WAP514', 'WAP515', 'WAP516',\n",
" 'WAP517', 'WAP518', 'WAP519', 'WAP520', 'LONGITUDE', 'LATITUDE',\n",
" 'FLOOR', 'BUILDINGID', 'SPACEID', 'RELATIVEPOSITION', 'USERID',\n",
" 'PHONEID', 'TIMESTAMP'], dtype=object)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Check the columns names\n",
"col_names = trainingData.columns.values\n",
"col_names"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Percent of missing data = 0.0%\n"
]
}
],
"source": [
"#check for missing values\n",
"missing_values_count = trainingData.isnull().sum()\n",
"#uncomment this if you want to see the count of missing data per column\n",
"#missing_values_count\n",
"\n",
"# how many total missing values do we have?\n",
"total_cells = np.product(trainingData.shape)\n",
"total_missing = missing_values_count.sum()\n",
"\n",
"# percent of data that is missing\n",
"missing_percent = (total_missing/total_cells) * 100\n",
"\n",
"print('Percent of missing data = {}%'.format(missing_percent))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** This information is not quite true, we have quite a bit of information missing in the WAP Columns. However, given the sparse disrtibution of WAP data, I would like to preserve those values as they are for now, there will be more feature engineering later."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Unique Floors : [2 0 3 4 1]\n",
"Unique Buildings : [1 0 2]\n",
"Unique Space IDs : [106 103 102 122 105 101 112 104 110 108 109 111 107 15 29 117 16 28\n",
" 22 10 2 4 3 5 6 9 27 8 7 26 18 216 17 217 247 248\n",
" 246 245 244 243 242 241 240 201 202 204 203 205 207 206 209 211 208 210\n",
" 212 214 213 215 121 219 221 222 218 220 250 223 225 224 229 226 227 228\n",
" 233 231 230 232 236 235 234 237 238 239 141 140 143 113 114 116 115 120\n",
" 118 128 119 129 125 124 131 127 132 126 133 134 137 135 136 253 254 123\n",
" 130 138 139 142 146 147 249 144 1 30 25 13 12 11 14]\n",
"Unique Relative Positions : [2 1]\n",
"Unique Users : [ 2 11 3 4 5 6 7 8 9 16 10 12 13 14 15 1 17 18]\n"
]
}
],
"source": [
"#Assess unique values per building columns\n",
"unique_floors = trainingData[\"FLOOR\"].unique()\n",
"unique_bldgs = trainingData[\"BUILDINGID\"].unique()\n",
"unique_spaceid = trainingData[\"SPACEID\"].unique()\n",
"unique_rpos = trainingData[\"RELATIVEPOSITION\"].unique()\n",
"unique_users = trainingData[\"USERID\"].unique()\n",
"print('Unique Floors : {}'.format(unique_floors))\n",
"print('Unique Buildings : {}'.format(unique_bldgs))\n",
"print('Unique Space IDs : {}'.format(unique_spaceid))\n",
"print('Unique Relative Positions : {}'.format(unique_rpos))\n",
"print('Unique Users : {}'.format(unique_users))\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#Map the data i.e. see the campus\n",
"trainingData.plot(kind=\"scatter\", x=\"LONGITUDE\", y=\"LATITUDE\", alpha=0.2)\n",
"plt.savefig('data_map.png')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 720x504 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#map the data by user ID\n",
"#i.e. see how much of the information in each building was collected by how many users\n",
"trainingData.plot(kind=\"scatter\", x=\"LONGITUDE\", y=\"LATITUDE\", alpha=0.4, figsize=(10,7),\n",
" c=\"USERID\", cmap=plt.get_cmap(\"jet\"), colorbar=True,\n",
" sharex=False)\n",
"plt.savefig('user_map2.png')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Comment:** We can clearly see that the data in each building was collected by only a handful of the users and that not all users walked around all buildings. This can result in highly skewed data, therefore, I will choose to discard of the User ID variable. "
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x2291c610b38>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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