Use LightGBM to model the normalized activations of the Autoencoder

modeling_activations_with_lightgbm.py

import lightgbm as lgb

params = {
        'max_depth': 7,
        'eta': 0.025,
        'objective': 'multiclass',
        'num_class': 5,
        'metric' : 'multi_logloss',
        'num_leaves' : 45,
        'bagging_fraction' : 0.5,
        'lambda_l2': 200,
        'max_bin': 100000,
        'feature_fraction':0.05,
        }

model = lgb.train(
params,
dtrain,
num_boost_round=10000,
early_stopping_rounds=200,
valid_sets=[dtrain, dval])