def predict(self, X):
        # Check data
        X = self._validate_X_predict(X)

        # Assign chunk of trees to jobs
        n_jobs, _, _ = _partition_estimators(self.n_estimators, self.n_jobs)

        # Parallel loop
        all_y_hat = Parallel(n_jobs=n_jobs, verbose=self.verbose,
                             backend="threading")(
            delayed(parallel_helper)(e, 'predict', X, check_input=False)
            for e in self.estimators_)

        # Reduce
        y_hat = sum(all_y_hat) / len(self.estimators_)

        return y_hat
Testing `transform` method (SRID match)
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/ensemble/forest.py/ForestRegressor.predict--crossover with--dataset/ETHPy150Open AppScale/appscale/AppServer/lib/django-1.4/django/contrib/gis/geos/tests/test_geos.py/GEOSTest.test23_transform_noop