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EXPERIMENT: CML Use-case -- Change classifier #62

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EXPERIMENT: CML Use-case -- Change classifier #62

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32 changes: 16 additions & 16 deletions cml_example/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -46,23 +46,23 @@
###############################################################################
# Train a scikit-learn estimator model -- assuming as .predict_proba
print("Training model")
model = LogisticRegression(
C=50. / train_samples,
penalty='l1',
solver='saga',
tol=0.1,
# important to make model training some sort of deterministic
random_state=0,
)
# model = MLPClassifier(
# hidden_layer_sizes=(50,),
# # max_iter=10,
# alpha=1e-4,
# solver='sgd',
# verbose=10,
# random_state=1,
# learning_rate_init=.1
# model = LogisticRegression(
# C=50. / train_samples,
# penalty='l1',
# solver='saga',
# tol=0.1,
# # important to make model training some sort of deterministic
# random_state=0,
# )
model = MLPClassifier(
hidden_layer_sizes=(50,),
# max_iter=10,
alpha=1e-4,
solver='sgd',
verbose=10,
random_state=1,
learning_rate_init=.1
)
model.fit(X_train, y_train)
print("Training model -- Done")

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