Classifier

class capymoa.base.Classifier

Bases: ABC

Base class for classifiers.

In machine learning, a classifier is a supervised learner that assigns a label to an instance. The label can be a class, a category, or other nominal value.

__init__(schema: Schema, random_seed: int = 1)

random_seed: int

The random seed for reproducibility.

When implementing a classifier ensure random number generators are seeded.

schema: Schema

The schema representing the instances.

abstract train(instance: LabeledInstance) → None

Train the classifier with a labeled instance.

Parameters:

instance – The labeled instance to train the classifier with.

abstract predict_proba(

instance: Instance,

) → ndarray[Any, dtype[float64]] | None

Return probability estimates for each label.

Parameters:

instance – The instance to estimate the probabilities for.

Returns:

An array of probabilities for each label or None if the classifier is unable to make a prediction.

predict(instance: Instance) → int | None

Predict the label of an instance.

The base implementation calls predict_proba() and returns the label with the highest probability.

Parameters:

instance – The instance to predict the label for.

Returns:

The predicted label or None if the classifier is unable to make a prediction.