python-scikit-learnAdaboost regression example
from sklearn import datasets, ensemble, model_selection
X, y = datasets.load_diabetes(return_X_y=True)
X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y)
model = ensemble.AdaBoostRegressor()
model.fit(X_train, y_train)
score = model.score(X_test, y_test)ctrl + cfrom sklearn importimport module from scikit-learn | model_selection.train_test_splitsplits given |
datasets.load_diabetesloads sample diabetes database | .AdaBoostRegressor(creates adaptive boosting regression model |
.fit(train model with a given features and target variable dataset | .score(returns model accuracy score |
Usage example
from sklearn import datasets, ensemble, model_selection
X, y = datasets.load_diabetes(return_X_y=True)
X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y)
model = ensemble.AdaBoostRegressor()
model.fit(X_train, y_train)
print(model.score(X_test, y_test))output
0.3076113179240463
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