Python StackingClassifier.get_params Examples

Example #1

def test_get_params():
    clf1 = KNeighborsClassifier(n_neighbors=1)
    clf2 = RandomForestClassifier(random_state=1)
    clf3 = GaussianNB()
    lr = LogisticRegression()
    sclf = StackingClassifier(classifiers=[clf1, clf2, clf3],
                              meta_classifier=lr)

    got = sorted(list({s.split('__')[0] for s in sclf.get_params().keys()}))
    expect = [
        'average_probas', 'classifiers', 'gaussiannb', 'kneighborsclassifier',
        'meta-logisticregression', 'meta_classifier', 'randomforestclassifier',
        'use_features_in_secondary', 'use_probas', 'verbose'
    ]
    assert got == expect, got

Example #2

File: test_stacking_classifier.py Project: thaolinhnp/Machine_Learning

def test_get_params():
    np.random.seed(123)
    clf1 = KNeighborsClassifier(n_neighbors=1)
    clf2 = RandomForestClassifier(n_estimators=10)
    clf3 = GaussianNB()
    lr = LogisticRegression(solver='liblinear', multi_class='ovr')
    sclf = StackingClassifier(classifiers=[clf1, clf2, clf3],
                              meta_classifier=lr)

    got = sorted(list({s.split('__')[0] for s in sclf.get_params().keys()}))
    expect = [
        'average_probas', 'classifiers', 'drop_last_proba', 'gaussiannb',
        'kneighborsclassifier', 'meta_classifier', 'randomforestclassifier',
        'store_train_meta_features', 'use_clones', 'use_features_in_secondary',
        'use_probas', 'verbose'
    ]
    assert got == expect, got

Example #3

File: test_stacking_classifier.py Project: venkatesh-1729/mlxtend

def test_get_params():
    clf1 = KNeighborsClassifier(n_neighbors=1)
    clf2 = RandomForestClassifier(random_state=1)
    clf3 = GaussianNB()
    lr = LogisticRegression()
    sclf = StackingClassifier(classifiers=[clf1, clf2, clf3],
                              meta_classifier=lr)

    got = sorted(list({s.split('__')[0] for s in sclf.get_params().keys()}))
    expect = ['average_probas',
              'classifiers',
              'gaussiannb',
              'kneighborsclassifier',
              'meta-logisticregression',
              'meta_classifier',
              'randomforestclassifier',
              'store_train_meta_features',
              'use_features_in_secondary',
              'use_probas',
              'verbose']
    assert got == expect, got

Example #4

File: test_stacking_classifier.py Project: rasbt/mlxtend

def test_get_params():
    np.random.seed(123)
    clf1 = KNeighborsClassifier(n_neighbors=1)
    clf2 = RandomForestClassifier(n_estimators=10)
    clf3 = GaussianNB()
    lr = LogisticRegression(solver='liblinear',
                            multi_class='ovr')
    sclf = StackingClassifier(classifiers=[clf1, clf2, clf3],
                              meta_classifier=lr)

    got = sorted(list({s.split('__')[0] for s in sclf.get_params().keys()}))
    expect = ['average_probas',
              'classifiers',
              'drop_last_proba',
              'gaussiannb',
              'kneighborsclassifier',
              'meta_classifier',
              'randomforestclassifier',
              'store_train_meta_features',
              'use_clones',
              'use_features_in_secondary',
              'use_probas',
              'verbose']
    assert got == expect, got