Expects ------- * Should early after fitting 2 models

Expects ------- * Two runs with the same id's should be considered equal * Otherwise, they should be considered different

Makes sure we raise a proper message to the user, when providing not supported data input or using the validator in a way that is not exp

Check if we can fit in a given type (numpy) yet transform if the user changes the type (pandas then)

Makes sure that encoded columns are returned by get_feat_type_from_columns whereas numerical columns are not returned

Test that the classifier components can be found Expects ------- * At least two classifier components can be found *

Test that preproccesor components can be found Expects ------- * At least 1 preprocessor component can be found * The

Tests by handing in predictions which contain NaNs

Test that all pipelines work with 1d target types Parameters ---------- regressor: RegressorChoice The regressor to test X:

Test that all pipelines work with 1d target types when they are wrapped as 2d Parameters ---------- regressor: RegressorChoice Th

Test that all pipelines work with 2d target types Parameters ---------- regressor: RegressorChoice The regressor to test X:

Expects ------- * Should favour 1) function kwargs, 2) function params 3) init_kwargs 4) init_params

Expects ------- * Should produce an ensemble if all runs have predictions

Expects ------- * If no ensemble targets can be found then `fit_ensemble` should fail

Make sure that if a preprocessor is added, it's fit method is called

Parameters ---------- mock_reduce_dataset: MagicMock A mock function to view call X_type: Union[np.ndarray, csr_matrix, list

Parameters ---------- dataset_compression: Dict The dataset_compression arg with "precision" set in it Fixtures --------

Tests that we can query the configuration space, and from the default configuration space, fit a classification pipeline with an acceptable s

Parameters ---------- dataset : str The name of the dataset task : int The task type of the dataset bounds : Tu

Expects ------- * A run without predictions will raise an error will cause `fit_ensemble` to fail as it requires all runs to have v

Test the configuration space returned by a SimpleClassificationPipeline Expects ------- * pipeline returns a configurations s

Test the configuration space when using include and exclude Expects ------- * Including a classifier has pipeline give back m

Test that invalid pipeline configurations raise errors Expects ------- * 0 combinations are found with 'multinomial_nb' and '

Test that the default classifier gets updated based on the legal feature preprocessors that come before. Expects -------