How to use Adaboost Classifier and Regressor in Python?
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How to use Adaboost Classifier and Regressor in Python?

This recipe helps you use Adaboost Classifier and Regressor in Python
In [1]:
## How to use Adaboost Classifier and Regressor in Python
def Snippet_162():
    print()
    print(format('How to use Adaboost Classifier and Regressor in Python','*^82'))

    import warnings
    warnings.filterwarnings("ignore")

    # load libraries
    from sklearn import datasets
    from sklearn import metrics
    from sklearn.ensemble import AdaBoostClassifier
    from sklearn.ensemble import AdaBoostRegressor
    from sklearn.model_selection import train_test_split
    import matplotlib.pyplot as plt
    import seaborn as sns

    plt.style.use('ggplot')

    # load the iris datasets
    dataset = datasets.load_iris()
    X = dataset.data; y = dataset.target
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25)

    # fit a CART model to the data
    model = AdaBoostClassifier()
    model.fit(X_train, y_train)
    print(); print(model)

    # make predictions
    expected_y  = y_test
    predicted_y = model.predict(X_test)

    # summarize the fit of the model
    print(); print(metrics.classification_report(expected_y, predicted_y))
    print(); print(metrics.confusion_matrix(expected_y, predicted_y))

    # load the boston datasets
    dataset = datasets.load_boston()
    X = dataset.data; y = dataset.target
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25)

    # fit a CART model to the data
    model = AdaBoostRegressor()
    model.fit(X_train, y_train)
    print(); print(model)

    # make predictions
    expected_y  = y_test
    predicted_y = model.predict(X_test)

    # summarize the fit of the model
    print(); print(metrics.r2_score(expected_y, predicted_y))
    print(); print(metrics.mean_squared_log_error(expected_y, predicted_y))

    # plot regression
    plt.figure(figsize=(10,10))
    sns.regplot(expected_y, predicted_y, fit_reg=True, scatter_kws={"s": 100})

Snippet_162()
**************How to use Adaboost Classifier and Regressor in Python**************

AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None,
          learning_rate=1.0, n_estimators=50, random_state=None)

              precision    recall  f1-score   support

           0       1.00      1.00      1.00        16
           1       0.60      1.00      0.75         6
           2       1.00      0.75      0.86        16

   micro avg       0.89      0.89      0.89        38
   macro avg       0.87      0.92      0.87        38
weighted avg       0.94      0.89      0.90        38


[[16  0  0]
 [ 0  6  0]
 [ 0  4 12]]

AdaBoostRegressor(base_estimator=None, learning_rate=1.0, loss='linear',
         n_estimators=50, random_state=None)

0.8109522137559658

0.034124635515305146