IProbabilisticClassifier#

class anomalearn.algorithms.IProbabilisticClassifier.IProbabilisticClassifier#

Bases: IClassifier

Interface identifying a machine learning probabilistic classifier.

List of decorated methods

predict_proba(x, *args, **kwargs)

Computes the probabilities for the given points.

List of inherited decorated methods

classify(x, *args, **kwargs)

Computes the labels for the given points.

Decorated methods

abstract predict_proba(x, *args, **kwargs) → ndarray#

Computes the probabilities for the given points.

Parameters:

  • x (array-like) – The data to be classified. Data must have at least two dimensions in which the first dimension represent the number of samples.

  • args – Not used, present to allow multiple inheritance and signature change.

  • kwargs – Not used, present to allow multiple inheritance and signature change.

Returns:

probabilities – The probabilities of points. The array must have at least 2 dimensions in which the first is equal to the first dimension of x (usually, it has 2 dimensions and the second is equal to the number of features in x).

Return type:

ndarray

Inherited decorated methods

abstract classify(x, *args, **kwargs) → ndarray#

Computes the labels for the given points.

Parameters:

  • x (array-like) – The data to be classified. Data must have at least two dimensions in which the first dimension represent the number of samples.

  • args – Not used, present to allow multiple inheritance and signature change.

  • kwargs – Not used, present to allow multiple inheritance and signature change.

Returns:

labels – The labels resulted from the classification. The array must have at least 2 dimensions in which the first is equal to the first dimension of x (usually, it has 2 dimensions and the second is 1).

Return type:

ndarray