mlrl.testbed_sklearn.experiments.output.characteristics.data package

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

Provides classes that allow to write characteristics of tabular datasets or predictions to different sinks.

class mlrl.testbed_sklearn.experiments.output.characteristics.data.DataCharacteristics(values: list[tuple[Characteristic, Any]])

Bases: TabularOutputData

Represents characteristics of a tabular dataset that are part of output data.

CONTEXT = Context(include_dataset_type=False, include_prediction_scope=True, include_fold=True)

OPTION_EXAMPLES = 'examples'

OPTION_FEATURES = 'features'

OPTION_FEATURE_DENSITY = 'feature_density'

OPTION_FEATURE_SPARSITY = 'feature_sparsity'

OPTION_NOMINAL_FEATURES = 'nominal_features'

OPTION_NUMERICAL_FEATURES = 'numerical_features'

OPTION_ORDINAL_FEATURES = 'ordinal_features'

PROPERTIES = TabularProperties(name='Data characteristics', file_name='data_characteristics', has_header=True)

static from_dataset(problem_domain: ProblemDomain, dataset: TabularDataset) → DataCharacteristics

Creates and returns DataCharacteristics from a given dataset.

Parameters:

• problem_domain – The problem domain, the dataset is concerned with

• dataset – The dataset

Returns:

The DataCharacteristics that have been created

to_table(options: Options, **kwargs) → Table | None

See mlrl.testbed.experiments.output.data.TabularOutputData.to_table()

to_text(options: Options, **kwargs) → str | None

See mlrl.testbed.experiments.output.data.TextualOutputData.to_text()

class mlrl.testbed_sklearn.experiments.output.characteristics.data.DataCharacteristicsWriter(*extractors: DataExtractor)

Bases: ResultWriter

Allows writing characteristics of a dataset to one or several sinks.

class DefaultExtractor

Bases: DataExtractor

The extractor to be used by a DataCharacteristicsWriter, by default.

extract_data(state: ExperimentState, _: list[Sink]) → list[tuple[ExperimentState, OutputData]]

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

class InputExtractor(properties: TabularProperties, context: Context)

Bases: TabularDataExtractor

Uses TabularInputData that has previously been loaded via an input reader.

extract_data(state: ExperimentState, sinks: list[Sink]) → list[tuple[ExperimentState, OutputData]]

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

class mlrl.testbed_sklearn.experiments.output.characteristics.data.OutputCharacteristics(values: list[tuple[Characteristic, Any]], properties: Properties, context: Context = Context(include_dataset_type=True, include_prediction_scope=True, include_fold=True))

Bases: TabularOutputData

Represents characteristics of an output matrix that are part of output data.

OPTION_DISTINCT_LABEL_VECTORS = 'distinct_label_vectors'

OPTION_LABEL_CARDINALITY = 'label_cardinality'

OPTION_LABEL_IMBALANCE_RATIO = 'label_imbalance_ratio'

OPTION_OUTPUTS = 'outputs'

OPTION_OUTPUT_DENSITY = 'output_density'

OPTION_OUTPUT_SPARSITY = 'output_sparsity'

to_table(options: Options, **kwargs) → Table | None

See mlrl.testbed.experiments.output.data.TabularOutputData.to_table()

to_text(options: Options, **kwargs) → str | None

See mlrl.testbed.experiments.output.data.TextualOutputData.to_text()

class mlrl.testbed_sklearn.experiments.output.characteristics.data.PredictionCharacteristicsWriter(*extractors: DataExtractor)

Bases: ResultWriter

Allows to write the characteristics of binary predictions to one or several sinks.

class DefaultExtractor

Bases: DataExtractor

The extractor to be used by a PredictionCharacteristicsWriter, by default.

extract_data(state: ExperimentState, _: list[Sink]) → list[tuple[ExperimentState, OutputData]]

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

class InputExtractor(properties: TabularProperties, context: Context)

Bases: TabularDataExtractor

Uses TabularInputData that has previously been loaded via an input reader.

extract_data(state: ExperimentState, sinks: list[Sink]) → list[tuple[ExperimentState, OutputData]]

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

Submodules

• mlrl.testbed_sklearn.experiments.output.characteristics.data.characteristics module
  • Characteristic
    • Characteristic.Function
  • OutputCharacteristics
    • OutputCharacteristics.OPTION_DISTINCT_LABEL_VECTORS
    • OutputCharacteristics.OPTION_LABEL_CARDINALITY
    • OutputCharacteristics.OPTION_LABEL_IMBALANCE_RATIO
    • OutputCharacteristics.OPTION_OUTPUTS
    • OutputCharacteristics.OPTION_OUTPUT_DENSITY
    • OutputCharacteristics.OPTION_OUTPUT_SPARSITY
    • OutputCharacteristics.to_table()
    • OutputCharacteristics.to_text()
  • get_output_characteristics()
• mlrl.testbed_sklearn.experiments.output.characteristics.data.characteristics_data module
  • DataCharacteristics
    • DataCharacteristics.CONTEXT
    • DataCharacteristics.OPTION_EXAMPLES
    • DataCharacteristics.OPTION_FEATURES
    • DataCharacteristics.OPTION_FEATURE_DENSITY
    • DataCharacteristics.OPTION_FEATURE_SPARSITY
    • DataCharacteristics.OPTION_NOMINAL_FEATURES
    • DataCharacteristics.OPTION_NUMERICAL_FEATURES
    • DataCharacteristics.OPTION_ORDINAL_FEATURES
    • DataCharacteristics.PROPERTIES
    • DataCharacteristics.from_dataset()
    • DataCharacteristics.to_table()
    • DataCharacteristics.to_text()
• mlrl.testbed_sklearn.experiments.output.characteristics.data.characteristics_prediction module
  • PredictionCharacteristics
    • PredictionCharacteristics.CONTEXT
    • PredictionCharacteristics.PROPERTIES
    • PredictionCharacteristics.from_prediction_matrix()
• mlrl.testbed_sklearn.experiments.output.characteristics.data.extension module
  • TabularDataCharacteristicExtension
    • TabularDataCharacteristicExtension.PRINT_DATA_CHARACTERISTICS
    • TabularDataCharacteristicExtension.SAVE_DATA_CHARACTERISTICS
    • TabularDataCharacteristicExtension.configure_experiment()
    • TabularDataCharacteristicExtension.get_supported_modes()
• mlrl.testbed_sklearn.experiments.output.characteristics.data.extension_prediction module
  • PredictionCharacteristicsExtension
    • PredictionCharacteristicsExtension.PRINT_PREDICTION_CHARACTERISTICS
    • PredictionCharacteristicsExtension.SAVE_PREDICTION_CHARACTERISTICS
    • PredictionCharacteristicsExtension.configure_experiment()
    • PredictionCharacteristicsExtension.get_supported_modes()
• mlrl.testbed_sklearn.experiments.output.characteristics.data.matrix_feature module
  • FeatureMatrix
    • FeatureMatrix.feature_density
    • FeatureMatrix.feature_sparsity
    • FeatureMatrix.num_examples
    • FeatureMatrix.num_features
    • FeatureMatrix.num_nominal_features
    • FeatureMatrix.num_numerical_features
    • FeatureMatrix.num_ordinal_features
• mlrl.testbed_sklearn.experiments.output.characteristics.data.matrix_label module
  • LabelMatrix
    • LabelMatrix.avg_label_cardinality
    • LabelMatrix.avg_label_imbalance_ratio
    • LabelMatrix.num_distinct_label_vectors
• mlrl.testbed_sklearn.experiments.output.characteristics.data.matrix_output module
  • OutputMatrix
    • OutputMatrix.num_outputs
    • OutputMatrix.output_density
    • OutputMatrix.output_sparsity
  • density()
• mlrl.testbed_sklearn.experiments.output.characteristics.data.writer_data module
  • DataCharacteristicsWriter
    • DataCharacteristicsWriter.DefaultExtractor
      • DataCharacteristicsWriter.DefaultExtractor.extract_data()
    • DataCharacteristicsWriter.InputExtractor
      • DataCharacteristicsWriter.InputExtractor.extract_data()
• mlrl.testbed_sklearn.experiments.output.characteristics.data.writer_prediction module
  • PredictionCharacteristicsWriter
    • PredictionCharacteristicsWriter.DefaultExtractor
      • PredictionCharacteristicsWriter.DefaultExtractor.extract_data()
    • PredictionCharacteristicsWriter.InputExtractor
      • PredictionCharacteristicsWriter.InputExtractor.extract_data()