def bench_scikit_tree_regressor(X, Y):
 from sklearn.tree import DecisionTreeRegressor
 gc.collect()
 tstart = datetime.now()
 clf = DecisionTreeRegressor()
 clf.fit(X, Y).predict(X)
 delta = (datetime.now() - tstart)
 scikit_regressor_results.append((delta.seconds + (delta.microseconds / mu_second)))

def bench_scikit_tree_regressor ( X , Y ) : from sklearn . tree import DecisionTreeRegressor gc . collect ( ) tstart = datetime . now ( ) clf = DecisionTreeRegressor ( ) clf . fit ( X , Y ) . predict ( X ) delta = ( datetime . now ( ) - tstart ) scikit_regressor_results . append ( ( delta . seconds + ( delta . microseconds / mu_second ) ) )
benchmark with scikit-learn decision tree regressor .