Exemplo n.º 1
0
    def _validate_and_set_permitted_range(self, params):
        """Validate and set the dictionary of permitted ranges for continuous features."""
        input_permitted_range = None
        if 'permitted_range' in params:
            input_permitted_range = params['permitted_range']

            if not hasattr(self, 'feature_names'):
                raise SystemException(
                    'Feature names not correctly set in public data interface')

            for input_permitted_range_feature_name in input_permitted_range:
                if input_permitted_range_feature_name not in self.feature_names:
                    raise UserConfigValidationException(
                        "permitted_range contains some feature names which are not part of columns in dataframe"
                    )
        self.permitted_range, _ = self.get_features_range(
            input_permitted_range)
Exemplo n.º 2
0
    def _validate_and_set_continuous_features_precision(self, params):
        """Validate and set the dictionary of precision for continuous features."""
        if 'continuous_features_precision' in params:
            self.continuous_features_precision = params[
                'continuous_features_precision']

            if not hasattr(self, 'feature_names'):
                raise SystemException(
                    'Feature names not correctly set in public data interface')

            for continuous_features_precision_feature_name in self.continuous_features_precision:
                if continuous_features_precision_feature_name not in self.feature_names:
                    raise UserConfigValidationException(
                        "continuous_features_precision contains some feature names which are not part of columns in dataframe"
                    )
        else:
            self.continuous_features_precision = None
Exemplo n.º 3
0
 def get_num_output_nodes2(self, input):
     if self.model_type == ModelTypes.Regressor:
         raise SystemException('Number of output nodes not supported for regression')
     return self.get_output(input).shape[1]