Multivariate Pattern Analysis in Python

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# mvpa2.featsel.helpers

Functions

`floor`(x) | Return the floor of x as a float.

Classes

`AttrDataset`(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes.
`BestDetector`([func, lastminimum]) | Determine whether the last value in a sequence is the best one given some criterion.
`ClassWithCollections`([descr]) | Base class for objects which contain any known collection Classes inherited from this class gain ability to access collections and their items as simple attributes.
`ConditionalAttribute`([enabled]) | Simple container intended to conditionally store the value ..
`ElementSelector`([mode]) | Base class to implement functors to select some elements based on a sequence of values.
`FixedErrorThresholdStopCrit`(threshold) | Stop computation if the latest error drops below a certain threshold.
`FixedNElementTailSelector`(nelements, **kwargs) | Given a sequence, provide set of IDs for a fixed number of to be selected elements.
`FractionTailSelector`(felements, **kwargs) | Given a sequence, provide Ids for a fraction of elements ..
`MultiStopCrit`(crits[, mode]) | Stop computation if the latest error drops below a certain threshold.
`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.
`NStepsStopCrit`(steps) | Stop computation after a certain number of steps.
`RangeElementSelector`([lower, upper, ...]) | Select elements based on specified range of values ..
`StoppingCriterion` | Base class for all functors to decide when to stop RFE (or may be general optimization...
`TailSelector`([tail, sort]) | Select elements from a tail of a distribution.

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