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Fix xgboost example for hyperparameter tuning #476

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merged 4 commits into from
Jan 15, 2019
Merged

Fix xgboost example for hyperparameter tuning #476

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9e1ee20
Fix xgboost for hp tuning
richardsliu Jan 14, 2019
8437ec9
Fix logging
richardsliu Jan 14, 2019
1b29c21
Merge remote-tracking branch 'upstream/master' into hp_tuning
richardsliu Jan 15, 2019
3859564
Fix pylint and log fmt
richardsliu Jan 15, 2019
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Fix xgboost for hp tuning
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@richardsliu
richardsliu committed Jan 14, 2019
commit 9e1ee205126e6b8bf78baf7e1fcdc3ea49cd9852
5 changes: 3 additions & 2 deletions xgboost_ames_housing/housing.py
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Expand Up @@ -30,7 +30,8 @@ def read_input(file_name, test_size=0.25):

train_X, test_X, train_y, test_y = train_test_split(X.values,
y.values,
test_size=test_size)
test_size=test_size,
shuffle=False)

imputer = Imputer()
train_X = imputer.fit_transform(train_X)
Expand Down Expand Up @@ -61,7 +62,7 @@ def train_model(train_X,
def eval_model(model, test_X, test_y):
"""Evaluate the model performance."""
predictions = model.predict(test_X)
print("MAE on test: {:.2f}".format(mean_absolute_error(predictions, test_y)))
print("mean_absolute_error={:.2f}".format(mean_absolute_error(predictions, test_y)))
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Should we use the logging module rather than print?

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Fixed


def save_model(model, model_file):
"""Save XGBoost model for serving."""
Expand Down