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netsatsawat/sgd_sklearn.py

Created August 5, 2020 10:10
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Snippet of SGD regressor implementation using sklearn
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sgd_sklearn.py
from sklearn.linear_model import SGDRegressor
SGD_rgs_normal = SGDRegressor(fit_intercept=True, random_state=SEED, eta0=learning_rate,
learning_rate='constant', max_iter=n_epochs)
SGD_rgs_normal.fit(X, y)
print(SGD_rgs_normal)
print(f'Intercept: {SGD_rgs_normal.intercept_}, weights: {SGD_rgs_normal.coef_}')
y_pred = SGD_rgs_normal.predict(X)
_ = print_regress_metric(y, y_pred)
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