5e52906d83e0ea6d7878be5dcd16d5b856ac3999,tests.py,,test_predict_proba2,#,201

Before Change

    Assert that the TPOT predict_proba function returns a numpy matrix filled with probabilities (float)

    tpot_obj = TPOTClassifier()
    tpot_obj._optimized_pipeline = creator.Individual. \
        from_string("GaussianNB(input_matrix)", tpot_obj._pset)
    tpot_obj._fitted_pipeline = tpot_obj._toolbox.compile(expr=tpot_obj._optimized_pipeline)
    tpot_obj._fitted_pipeline.fit(training_features, training_classes)

    result = tpot_obj.predict_proba(testing_features)

After Change

    Assert that the TPOT predict_proba function returns a numpy matrix filled with probabilities (float)

    tpot_obj = TPOTClassifier()
    np.random.seed(53)
    tpot_obj._optimized_pipeline = tpot_obj._toolbox.individual()
    tpot_obj._fitted_pipeline = tpot_obj._toolbox.compile(expr=tpot_obj._optimized_pipeline)
    tpot_obj._fitted_pipeline.fit(training_features, training_classes)

Instances