9d677b56f4244eb08f1c7e2061a1e86fd0aee748,examples/compose/plot_column_transformer_mixed_types.py,,,#,38

Before Change

clf = Pipeline(steps=[("preprocessor", preprocessor),
                      ("classifier", LogisticRegression())])

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)

clf.fit(X_train, y_train)
print("model score: %.3f" % clf.score(X_test, y_test))

After Change

grid_search.fit(X_train, y_train)

print(f"Best params:")
print(grid_search.best_params_)

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// The internal cross-validation scores obtained by those parameters is:
print(f"Internal CV score: {grid_search.best_score_:.3f}")

Instances