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mloptimizer.evaluation.evaluator

mloptimizer.evaluation.evaluator#

Module Contents#

Classes#

Evaluator

Evaluator class to evaluate the performance of a classifier
class mloptimizer.evaluation.evaluator.Evaluator(features: numpy.array, labels: numpy.array, eval_function, fitness_score='accuracy', metrics=None, tracker: mloptimizer.aux.Tracker = None, individual_utils=None)[source]#

Evaluator class to evaluate the performance of a classifier

Parameters:

  • features (array-like) – The features to use to evaluate the classifier

  • labels (array-like) – The labels to use to evaluate the classifier

  • eval_function (function) – The evaluation function to use to evaluate the performance of the classifier

  • fitness_score (str) – The fitness score to use to evaluate the performance of the classifier

  • metrics (dict) – The metrics to use to evaluate the performance of the classifier Dictionary of the form {“metric_name”: metric_function}

  • tracker (Tracker) – The tracker to use to log the evaluations

  • individual_utils (IndividualUtils) – The individual utils to use to get the classifier from the individual

evaluate(clf, features, labels)[source]#

Evaluate the performance of a classifier

Parameters:

  • clf (object) – The classifier to evaluate

  • features (array-like) – The features to use to evaluate the classifier

  • labels (array-like) – The labels to use to evaluate the classifier

Returns:

metrics – Dictionary of the form {“metric_name”: metric_value}

Return type:

dict

evaluate_individual(individual)[source]#
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