python-scikit-learnDecision tree regression example
from sklearn import datasets, tree, 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 = tree.DecisionTreeRegressor()
model.fit(X_train, y_train)
score = model.score(X_test, y_test)ctrl + cfrom sklearn importimport module from scikit-learn | datasets.load_diabetesloads sample diabetes database |
model_selection.train_test_splitsplits given | .DecisionTreeRegressor(creates decision tree regression model |
.fit(train model with a given features and target variable dataset | .score(returns model accuracy score |
Usage example
from sklearn import datasets, tree, 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 = tree.DecisionTreeRegressor()
model.fit(X_train, y_train)
print(model.score(X_test, y_test))output
-0.1321271764882921
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