`skactiveml.utils`#

The skactiveml.utils module includes various utilities.

Classes#

utils.ExtLabelEncoder

Encode class labels with value between 0 and classes-1 and uses -1 for unlabeled samples.

Functions#

`utils.rand_argmax`	Returns index of maximum value.
`utils.rand_argmin`	Returns index of minimum value.
`utils.compute_vote_vectors`	Counts number of votes per class label for each sample.
`utils.majority_vote`	Assigns a label to each sample based on weighted voting.
`utils.is_unlabeled`	Creates a boolean mask indicating missing labels.
`utils.is_labeled`	Creates a boolean mask indicating present labels.
`utils.check_classes`	Check whether class labels are uniformly strings or numbers.
`utils.check_missing_label`	Check whether a missing label is compatible to a given target type.
`utils.check_cost_matrix`	Check whether cost matrix has shape (n_classes, n_classes).
`utils.check_scalar`	Validate scalar parameters type and value.
`utils.check_classifier_params`	Check whether the parameters are compatible to each other (only if classes is not None).
`utils.check_X_y`	Input validation for standard estimators.
`utils.check_random_state`	Check validity of the given random state.
`utils.call_func`	Calls a function with the given parameters given in kwargs, if they exist as parameters in f_callable.
`utils.match_signature`	A decorator that matches the signature to a given method from a reference and hides it when the reference object does not have the wrapped function.
`utils.check_class_prior`	Check if the class_prior is a valid prior.
`utils.ext_confusion_matrix`	Compute confusion matrix [R3479f72bc894-1] to evaluate the accuracy of a classification.
`utils.labeled_indices`	Return an array of indices indicating present labels.
`utils.unlabeled_indices`	Return an array of indices indicating missing labels.
`utils.check_type`	Check if obj is one of the given types.
`utils.check_bound`	Validates bound and returns the bound of X if bound is None.
`utils.check_equal_missing_label`	Check whether two missing label values are equal to each other.
`utils.check_budget_manager`	Validate if budget_manager is a budget manager class and create a copy budget_manager_.
`utils.check_indices`	Check if indices fit to array.
`utils.simple_batch`	Generates a batch by selecting the highest values in the utilities.
`utils.check_n_features`	Validate and update the number of features for an estimator based on the input data.
`utils._check_callable`	Checks if func is a callable and if the number of free parameters is correct.
`utils._check_forward_outputs`	Check forward outputs required by SkorchMixin and make_criterion_tuple_aware.
`utils.make_criterion_tuple_aware`	Create a loss class (or wrap an existing instance) that selects part of a model's (possibly tuple-valued) output before passing it to the criterion.