mvpa2.featsel.baseΒΆ
Feature selection base class and related stuff base classes and helpers.
Functions
accepts_dataset_as_samples(fx) |
Decorator to extract samples from Datasets. |
mask2slice(mask) |
Convert a boolean mask vector into an equivalent slice (if possible). |
split_by_sample_attribute(ds, sa_label[, ...]) |
Splits a dataset based on unique values of a sample attribute |
vstack(datasets[, a, fa]) |
Stacks datasets vertically (appending samples). |
Classes
BestDetector([func, lastminimum]) |
Determine whether the last value in a sequence is the best one given some criterion. |
CombinedFeatureSelection(selectors, method, ...) |
Meta feature selection utilizing several embedded selection methods. |
ConditionalAttribute([enabled]) |
Simple container intended to conditionally store the value |
FeatureSelection([filler]) |
Mapper to select a subset of features. |
FractionTailSelector(felements, \*\*kwargs) |
Given a sequence, provide Ids for a fraction of elements |
IterativeFeatureSelection(fmeasure, ...[, ...]) |
Notes |
NBackHistoryStopCrit([bestdetector, steps]) |
Stop computation if for a number of steps error was increasing |
SensitivityBasedFeatureSelection(...[, ...]) |
Feature elimination. |
SliceMapper(slicearg, \*\*kwargs) |
Baseclass of Mapper that slice a Dataset in various ways. |
SplitSamplesProbabilityMapper(...[, ...]) |
Mapper to select features & samples based on some sensitivity value. |
StaticFeatureSelection(slicearg[, dshape, ...]) |
Feature selection by static slicing argument. |
