i.py

# Di kerjakan bersama : 
# - Izzeldin Addarda (41519010045)
# - Micheal Gunawan (41519010147)
# - Akbar Basyarudin (41519010046)
# - Fahad Hakim Mc (41519010061)
# - Dinda Arum Nugroho (41519010049)
# - Sandika Maulana (41519010066)
# - Bambang Subroto (41519010067) 


import pandas as pd
import sys
import numpy as np
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import MinMaxScaler
from sklearn.preprocessing import StandardScaler
data = pd.read_csv('train.csv')

scaler = MinMaxScaler()
X = data[['LotFrontage', 'LotArea']].astype(float).fillna(0)
Y = data['SalePrice'].astype(float).fillna(0)

new_X = np.array(StandardScaler().fit_transform(X)).reshape(2, -1)
new_Y = np.array(StandardScaler().fit_transform(Y.values.reshape(-1, 1)))
print()
B = np.dot(np.dot((np.dot(new_X.T, new_X)**-1), new_X.T).reshape(2, -1), new_Y)
print("B adalah\n", B)