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vanbrands/mlprod:pipeline2.py

Last active July 23, 2020 17:03
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mlprod:pipeline2.py
from sklearn.compose import ColumnTransformer
# Define you transformers.
preprocessing = ColumnTransformer(transformers=[
('encode_categorical_features', OneHotEncoder(), ['categorical_column'])
], remainder='passthrough')
estimator = GradientBoostingClassifier()
# Define steps in the pipeline.
pipeline = Pipeline(steps=[
('preprocessing', preprocessing),
('model', estimator)
])
pipeline.fit(x_train, y_train)
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