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Multivariate Pattern Analysis in Python |
Inheritance diagram for mvpa.measures.anova:
FeaturewiseDatasetMeasure performing a univariate ANOVA.
Bases: mvpa.measures.anova.OneWayAnova
Compound comparisons via univariate ANOVA.
Provides F-scores per each label if compared to the other labels.
Note
Available state variables:
(States enabled by default are listed with +)
Initialize
Parameters: |
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Bases: mvpa.measures.base.FeaturewiseDatasetMeasure
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.
Note
Available state variables:
(States enabled by default are listed with +)
See also
Please refer to the documentation of the base class for more information:
Initialize
Parameters: |
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