Class OneWayAnova

source code

FeaturewiseDatasetMeasure that performs a univariate ANOVA.

F-scores are computed for each feature as the standard fraction of between and within group variances. Groups are defined by samples with unique labels.

No statistical testing is performed, but raw F-scores are returned as a sensitivity map. As usual F-scores have a range of [0,inf] with greater values indicating higher sensitivity.

Nested Classes

[hide private]

Inherited from misc.state.ClassWithCollections: __metaclass__

Instance Methods

[hide private]

_call(self, dataset, labels=None)
Computes a per-feature-measure on a given Dataset.

source code

Inherited from base.FeaturewiseDatasetMeasure: __init__, __repr__, combiner

Inherited from base.FeaturewiseDatasetMeasure (private): _postcall

Inherited from base.DatasetMeasure: __call__, null_dist, transformer, untrain

Inherited from misc.state.ClassWithCollections: __getattribute__, __new__, __setattr__, __str__, reset

Inherited from object: __delattr__, __format__, __hash__, __reduce__, __reduce_ex__, __sizeof__, __subclasshook__

Class Variables

[hide private]

Inherited from base.FeaturewiseDatasetMeasure: base_sensitivities

Inherited from base.DatasetMeasure: __doc__, null_prob, null_t, raw_results

Inherited from misc.state.ClassWithCollections: _DEV__doc__, descr

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

_call(self, dataset, labels=None)

source code

Computes a per-feature-measure on a given Dataset.

Behaves like a DatasetMeasure, but computes and returns a 1d ndarray with one value per feature.

Overrides: base.DatasetMeasure._call: (inherited documentation)

Home

Trees

Indices

Help