Machine Learning for OpenCV

Implementing AdaBoost in scikit-learn

In scikit-learn, AdaBoost is just another ensemble estimator. We can create an ensemble from 100 decision stumps as follows:

In [6]: from sklearn.ensemble import AdaBoostClassifier...     ada = AdaBoostClassifier(n_estimators=100,...                              random_state=456)

We can load the breast cancer set once more and split it 75-25:

In [7]: from sklearn.datasets import load_breast_cancer...     cancer = load_breast_cancer()...     X = cancer.data...     y = cancer.targetIn [8]: from sklearn.model_selection import train_test_split...     X_train, X_test, y_train, y_test = train_test_split(...         X, y, random_state=456...     )

Then fit and score AdaBoost using the familiar procedure:

In [9]: ada.fit(X_train, y_train)... ada.score(X_test, y_test) ...