Multivariate Pattern Analysis in Python

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# mvpa2.generators.partition

Functions

`coarsen_chunks`(source[, nchunks]) | Change chunking of the dataset Group chunks into groups to match desired number of chunks.

Classes

`CustomPartitioner`(splitrule, **kwargs) | Partition a dataset using an arbitrary custom rule.
`ExcludeTargetsCombinationsPartitioner`(k, ...) | Exclude combinations for a given partition from other partitions Given a pre-generated partitioning this generates new partitions by selecting all possible combinations of k-targets from all targets and excluding samples with the selected k-targets from training partition for each combination.
`HalfPartitioner`([count, selection_strategy, ...]) | Partition a dataset into two halves of the sample attribute.
`NFoldPartitioner`([cvtype]) | Generic N-fold data partitioner.
`NGroupPartitioner`([ngroups]) | Partition a dataset into N-groups of the sample attribute.
`Node`([space, postproc]) | Common processing object.
`OddEvenPartitioner`([usevalues]) | Create odd and even partitions based on a sample attribute.
`Partitioner`([count, selection_strategy, ...]) | Generator node to partition a dataset.
`deprecated`([extra]) | Decorator to mark a function or class as deprecated.

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