Multivariate Pattern Analysis in Python

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# mvpa2.featsel.ifs

Incremental feature search (IFS).

Very similar to Recursive feature elimination (RFE), but instead of begining with all features and stripping some sequentially, start with an empty feature set and include important features successively.

Functions

`copy`(x) | Shallow copy operation on arbitrary Python objects.

Classes

`BestDetector`([func, lastminimum]) | Determine whether the last value in a sequence is the best one given some criterion.
`ConditionalAttribute`([enabled]) | Simple container intended to conditionally store the value ..
`FixedNElementTailSelector`(nelements, **kwargs) | Given a sequence, provide set of IDs for a fixed number of to be selected elements.
`IFS`(fmeasure, pmeasure, splitter[, fselector]) | Incremental feature search.
`IterativeFeatureSelection`(fmeasure, ...[, ...]) | Notes
`NBackHistoryStopCrit`([bestdetector, steps]) | Stop computation if for a number of steps error was increasing Initialize with number of steps :Parameters: bestdetector : BestDetector used to determine where the best error is located.
`StaticFeatureSelection`(slicearg[, dshape, ...]) | Feature selection by static slicing argument.

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