h2o-py/h2o/model/model_base.py
def show(self):
        """Print innards of model, without regards to type."""
        if self._future:
            self._job.poll_once()
            return
        if self._model_json is None:
            print("No model trained yet")
            return
        if self.model_id is None:
            print("This H2OEstimator has been removed.")
            return
        model = self._model_json["output"]
        print("Model Details")
        print("=============")

        print(self.__class__.__name__, ": ", self._model_json["algo_full_name"])
        print("Model Key: ", self._id)

        self.summary()

        print()
        # training metrics
        tm = model["training_metrics"]
        if tm: tm.show()
        vm = model["validation_metrics"]
        if vm: vm.show()
        xm = model["cross_validation_metrics"]
        if xm: xm.show()
        xms = model["cross_validation_metrics_summary"]
        if xms: xms.show()

        if "scoring_history" in model and model["scoring_history"]:
            model["scoring_history"].show()
        if "variable_importances" in model and model["variable_importances"]:
            model["variable_importances"].show()
def show(self):
        if self._future:
            self._job.poll_once()
            return
        if self._model_json is None:
            print("No model trained yet")
            return
        if self.model_id is None:
            print("This H2OEstimator has been removed.")
            return
        model = self._model_json["output"]
        print("Model Details")
        print("=============")

        print(self.__class__.__name__, ": ", self._model_json["algo_full_name"])
        print("Model Key: ", self._id)

        self.summary()

        print()
        # training metrics
        tm = model["training_metrics"]
        if tm: tm.show()
        vm = model["validation_metrics"]
        if vm: vm.show()
        xm = model["cross_validation_metrics"]
        if xm: xm.show()
        xms = model["cross_validation_metrics_summary"]
        if xms: xms.show()

        if "scoring_history" in model and model["scoring_history"]:
            model["scoring_history"].show()
        if "variable_importances" in model and model["variable_importances"]:
            model["variable_importances"].show()
def show ( self ) : if self . _future : self . _job . poll_once ( ) return if self . _model_json is None : print ( "No model trained yet" ) return if self . model_id is None : print ( "This H2OEstimator has been removed." ) return model = self . _model_json [ "output" ] print ( "Model Details" ) print ( "=============" ) print ( self . __class__ . __name__ , ": " , self . _model_json [ "algo_full_name" ] ) print ( "Model Key: " , self . _id ) self . summary ( ) print ( ) # training metrics tm = model [ "training_metrics" ] if tm : tm . show ( ) vm = model [ "validation_metrics" ] if vm : vm . show ( ) xm = model [ "cross_validation_metrics" ] if xm : xm . show ( ) xms = model [ "cross_validation_metrics_summary" ] if xms : xms . show ( ) if "scoring_history" in model and model [ "scoring_history" ] : model [ "scoring_history" ] . show ( ) if "variable_importances" in model and model [ "variable_importances" ] : model [ "variable_importances" ] . show ( )
Print innards of model, without regards to type.
Print innards of model without regards to type .