Ejemplos de TabularClassificationPipeline.get_fit_requirements en Python

Ejemplo n.º 1

    def test_get_fit_requirements(self):
        dataset_properties = {
            'numerical_columns': [],
            'categorical_columns': []
        }
        pipeline = TabularClassificationPipeline(
            dataset_properties=dataset_properties)
        fit_requirements = pipeline.get_fit_requirements()

        # check if fit requirements is a list of FitRequirement named tuples
        self.assertIsInstance(fit_requirements, list)
        for requirement in fit_requirements:
            self.assertIsInstance(requirement, FitRequirement)

Ejemplo n.º 2

Archivo: test_tabular_classification.py Proyecto: automl/Auto-PyTorch

    def test_get_fit_requirements(self, fit_dictionary_tabular):
        dataset_properties = {
            'numerical_columns': [],
            'categorical_columns': [],
            'task_type': 'tabular_classification'
        }
        pipeline = TabularClassificationPipeline(
            dataset_properties=dataset_properties)
        fit_requirements = pipeline.get_fit_requirements()

        # check if fit requirements is a list of FitRequirement named tuples
        assert isinstance(fit_requirements, list)
        for requirement in fit_requirements:
            assert isinstance(requirement, FitRequirement)