1b0d3a48e8bd7798576f8ae549586fe2d422151b,tests/flows/test_flow.py,TestFlow,test_sklearn_to_upload_to_flow,#TestFlow#Any#,134

Before Change

        scaler = sklearn.preprocessing.StandardScaler(with_mean=False)
        boosting = sklearn.ensemble.AdaBoostClassifier(
            base_estimator=sklearn.tree.DecisionTreeClassifier())
        model = sklearn.pipeline.Pipeline(steps=(
            ("scaler", scaler), ("boosting", boosting)))
        parameter_grid = {"boosting__n_estimators": [1, 5, 10, 100],
                          "boosting__learning_rate": scipy.stats.uniform(0.01, 0.99),
                          "boosting__base_estimator__max_depth": scipy.stats.randint(1, 10)}

After Change

        fs = sklearn.feature_selection.SelectPercentile(
            score_func=sklearn.feature_selection.f_classif, percentile=30)
        fu = sklearn.pipeline.FeatureUnion(transformer_list=[
            ("pca", pca), ("fs", fs)])
        boosting = sklearn.ensemble.AdaBoostClassifier(
            base_estimator=sklearn.tree.DecisionTreeClassifier())
        model = sklearn.pipeline.Pipeline(steps=[("ohe", ohe), ("scaler", scaler),
                                                 ("fu", fu), ("boosting", boosting)])
        parameter_grid = {"boosting__n_estimators": [1, 5, 10, 100],
                          "boosting__learning_rate": scipy.stats.uniform(0.01, 0.99),
                          "boosting__base_estimator__max_depth": scipy.stats.randint(1, 10)}
        cv = sklearn.model_selection.StratifiedKFold(n_splits=5, shuffle=True)

Instances