h2o-py/h2o/model/dim_reduction.py
def proj_archetypes(self, test_data, reverse_transform=False):
        """
        Convert archetypes of the model into original feature space.

        :param H2OFrame test_data: The dataset upon which the model was trained.
        :param bool reverse_transform: Whether the transformation of the training data during model-building
            should be reversed on the projected archetypes.

        :returns: model archetypes projected back into the original training data's feature space.
        """
        if test_data is None or test_data.nrow == 0: raise ValueError("Must specify test data")
        j = h2o.api("POST /3/Predictions/models/%s/frames/%s" % (self.model_id, test_data.frame_id),
                    data={"project_archetypes": True, "reverse_transform": reverse_transform})
        return h2o.get_frame(j["model_metrics"][0]["predictions"]["frame_id"]["name"])
def proj_archetypes(self, test_data, reverse_transform=False):
        if test_data is None or test_data.nrow == 0: raise ValueError("Must specify test data")
        j = h2o.api("POST /3/Predictions/models/%s/frames/%s" % (self.model_id, test_data.frame_id),
                    data={"project_archetypes": True, "reverse_transform": reverse_transform})
        return h2o.get_frame(j["model_metrics"][0]["predictions"]["frame_id"]["name"])
def proj_archetypes ( self , test_data , reverse_transform = False ) : if test_data is None or test_data . nrow == 0 : raise ValueError ( "Must specify test data" ) j = h2o . api ( "POST /3/Predictions/models/%s/frames/%s" % ( self . model_id , test_data . frame_id ) , data = { "project_archetypes" : True , "reverse_transform" : reverse_transform } ) return h2o . get_frame ( j [ "model_metrics" ] [ 0 ] [ "predictions" ] [ "frame_id" ] [ "name" ] )
Convert archetypes of the model into original feature space.

        :param H2OFrame test_data: The dataset upon which the model was trained.
        :param bool reverse_transform: Whether the transformation of the training data during model-building
            should be reversed on the projected archetypes.

        :returns: model archetypes projected back into the original training data's feature space.
Convert archetypes of the model into original feature space .