sklearn pipeline with interactions python
model_pipeline = Pipeline(steps=[
("dimension_reduction", PCA(n_components=10)),
("classifiers", RandomForestClassifier())
])
model_pipeline.fit(train_data.values, train_labels.values)
predictions = model_pipeline.predict(predict_data.values)Copyright © 2021 Codeinu
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