Module base

source code

Base class for data measures: algorithms that quantify properties of datasets.

Besides the DatasetMeasure base class this module also provides the (abstract) FeaturewiseDatasetMeasure class. The difference between a general measure and the output of the FeaturewiseDatasetMeasure is that the latter returns a 1d map (one value per feature in the dataset). In contrast there are no restrictions on the returned value of DatasetMeasure except for that it has to be in some iterable container.

Classes

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DatasetMeasure
A measure computed from a Dataset

FeaturewiseDatasetMeasure
A per-feature-measure computed from a Dataset (base class).

StaticDatasetMeasure
A static (assigned) sensitivity measure.

Sensitivity

CombinedFeaturewiseDatasetMeasure
Set sensitivity analyzers to be merged into a single output

SplitFeaturewiseDatasetMeasure
Compute measures across splits for a specific analyzer

BoostedClassifierSensitivityAnalyzer
Set sensitivity analyzers to be merged into a single output

ProxyClassifierSensitivityAnalyzer
Set sensitivity analyzer output just to pass through

MappedClassifierSensitivityAnalyzer
Set sensitivity analyzer output be reverse mapped using mapper of the slave classifier

FeatureSelectionClassifierSensitivityAnalyzer
Set sensitivity analyzer output be reverse mapped using mapper of the slave classifier

Imports: N, copy, StateVariable, ClassWithCollections, group_kwargs, FirstAxisMean, SecondAxisSumOfAbs, enhancedDocString, externals, warning, autoNullDist, debug

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