Ejemplo n.º 1
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def test_pybrain_classification():
    clf = PyBrainClassifier(epochs=2)
    check_classifier(clf, **classifier_params)
    check_classifier(
        PyBrainClassifier(epochs=-1, continue_epochs=1, layers=[]),
        **classifier_params)
    check_classifier(PyBrainClassifier(epochs=2, layers=[5, 2]),
                     **classifier_params)
Ejemplo n.º 2
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def test_pybrain_classification():
    check_classifier(PyBrainClassifier(),
                     has_staged_pp=False,
                     has_importances=False,
                     supports_weight=False)
    check_classifier(PyBrainClassifier(layers=[10, 10]),
                     has_staged_pp=False,
                     has_importances=False,
                     supports_weight=False)
Ejemplo n.º 3
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def test_simple_stacking_pybrain():
    base_pybrain = PyBrainClassifier()
    check_classifier(SklearnClassifier(
        clf=BaggingClassifier(base_estimator=base_pybrain, n_estimators=3)),
                     has_staged_pp=False,
                     has_importances=False,
                     supports_weight=False)
Ejemplo n.º 4
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def test_pybrain_reproducibility():
    # This test fails. Because PyBrain can't reproduce training.
    X, y, _ = generate_classification_data()
    clf1 = PyBrainClassifier(layers=[4], epochs=2).fit(X, y)
    clf2 = PyBrainClassifier(layers=[4], epochs=2).fit(X, y)
    print(clf1.predict_proba(X) - clf2.predict_proba(X))
    assert numpy.allclose(clf1.predict_proba(X),
                          clf2.predict_proba(X)), 'different predicitons'
    check_classification_reproducibility(clf1, X, y)
Ejemplo n.º 5
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def test_pybrain_Tanh():
    check_classifier(PyBrainClassifier(layers=[10], hiddenclass=['TanhLayer']),
                     has_staged_pp=False,
                     has_importances=False,
                     supports_weight=False)
    check_regression(PyBrainRegressor(layers=[10], hiddenclass=['TanhLayer']),
                     has_staged_predictions=False,
                     has_importances=False,
                     supports_weight=False)
Ejemplo n.º 6
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def test_pybrain_Linear_MDLSTM():
    check_classifier(
        PyBrainClassifier(epochs=2,
                          layers=[10, 2],
                          hiddenclass=['LinearLayer', 'MDLSTMLayer']),
        **classifier_params)
    check_regression(
        PyBrainRegressor(epochs=3,
                         layers=[10, 2],
                         hiddenclass=['LinearLayer', 'MDLSTMLayer']),
        **regressor_params)
Ejemplo n.º 7
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def test_pybrain_SoftMax_Tanh():
    check_classifier(
        PyBrainClassifier(epochs=10,
                          layers=[5, 2],
                          hiddenclass=['TanhLayer', 'SoftmaxLayer'],
                          use_rprop=True), **classifier_params)
    check_regression(
        PyBrainRegressor(
            epochs=2,
            layers=[10, 5, 2],
            hiddenclass=['TanhLayer', 'SoftmaxLayer', 'TanhLayer']),
        **regressor_params)
Ejemplo n.º 8
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def test_pybrain_reproducibility():
    # This test fails. Because PyBrain can't reproduce training.
    X, y, _ = generate_classification_data()
    clf1 = PyBrainClassifier(layers=[4], epochs=2).fit(X, y)
    clf2 = PyBrainClassifier(layers=[4], epochs=2).fit(X, y)
    print(clf1.predict_proba(X) - clf2.predict_proba(X))
    assert numpy.allclose(clf1.predict_proba(X), clf2.predict_proba(X)), 'different predicitons'
    check_classification_reproducibility(clf1, X, y)
Ejemplo n.º 9
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def test_pybrain_multi_classification():
    check_classifier(PyBrainClassifier(), n_classes=4, **classifier_params)
Ejemplo n.º 10
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def pybrain_test_partial_fit():
    clf = PyBrainClassifier(layers=[4], epochs=2)
    X, y, _ = generate_classification_data()
    clf.partial_fit(X, y)
    clf.partial_fit(X[:2], y[:2])
Ejemplo n.º 11
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def test_simple_stacking_pybrain():
    base_pybrain = PyBrainClassifier(epochs=2)
    base_bagging = BaggingClassifier(base_estimator=base_pybrain, n_estimators=3)
    check_classifier(SklearnClassifier(clf=base_bagging), **classifier_params)
Ejemplo n.º 12
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def test_pybrain_multiclassification():
    check_classifier(PyBrainClassifier(),
                     has_staged_pp=False,
                     has_importances=False,
                     supports_weight=False,
                     n_classes=4)
Ejemplo n.º 13
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def test_pybrain_rprop():
    check_classifier(PyBrainClassifier(use_rprop=True),
                     has_staged_pp=False,
                     has_importances=False,
                     supports_weight=False)