mlrl.boosting.testbed.experiments.output.probability_calibration.writer module

Author: Michael Rapp (michael.rapp.ml@gmail.com)

Provides classes that allow writing textual representations of probability calibration models to one or several sinks.

class mlrl.boosting.testbed.experiments.output.probability_calibration.writer.JointProbabilityCalibrationModelWriter(*extractors: DataExtractor)

Bases: ProbabilityCalibrationModelWriter

Allows writing textual representations of models for the calibration of joint probabilities to one or several sinks.

class DefaultExtractor

Bases: DefaultExtractor

Extracts isotonic regression models for the calibration of joint probabilities that are stores as part of a rule model.

class mlrl.boosting.testbed.experiments.output.probability_calibration.writer.MarginalProbabilityCalibrationModelWriter(*extractors: DataExtractor)

Bases: ProbabilityCalibrationModelWriter

Allows writing textual representations of models for the calibration of marginal probabilities to one or several sinks.

class DefaultExtractor

Bases: DefaultExtractor

Extracts isotonic regression models for the calibration of marginal probabilities that are stores as part of a rule model.

class mlrl.boosting.testbed.experiments.output.probability_calibration.writer.ProbabilityCalibrationModelWriter(*extractors: DataExtractor)

Bases: OutputWriter, ABC

Allows writing textual representations of probability calibration models to one or several sinks.

class DefaultExtractor

Bases: DataExtractor, ABC

An abstract base class for all classes that extract probability calibration models that are stored as part of a rule model.

extract_data(state: ExperimentState, _: List[Sink]) → OutputData | None

See mlrl.testbed.experiments.output.writer.DataExtractor.extract_data()