mvpa2.generators.partition.ExcludeTargetsCombinationsPartitioner

Inheritance diagram of ExcludeTargetsCombinationsPartitioner

class mvpa2.generators.partition.ExcludeTargetsCombinationsPartitioner(k, targets_attr, partitions_attr='partitions', partitions_keep=2, partition_assign=3, **kwargs)

Given a pre-generated partitioning XXX

TODO 4 Swaroop – provide documentation Example ——-

partitioner = ChainNode([NFoldPartitioner(),
ExcludeTargetsCombinationsPartitioner(
k=2, targets_attr=’targets’, space=’partitions’)],

space=’partitions’)

Notes

Available conditional attributes:

  • calling_time+: Time (in seconds) it took to call the node
  • raw_results: Computed results before invoking postproc. Stored only if postproc is not None.

(Conditional attributes enabled by default suffixed with +)

Initialize instance of ExcludeTargetsCombinationsPartitioner

Parameters :

enable_ca : None or list of str

Names of the conditional attributes which should be enabled in addition to the default ones

disable_ca : None or list of str

Names of the conditional attributes which should be disabled

space: str, optional :

Name of the ‘processing space’. The actual meaning of this argument heavily depends on the sub-class implementation. In general, this is a trigger that tells the node to compute and store information about the input data that is “interesting” in the context of the corresponding processing in the output dataset.

postproc : Node instance, optional

Node to perform post-processing of results. This node is applied in __call__() to perform a final processing step on the to be result dataset. If None, nothing is done.

descr : str

Description of the instance

generate(ds)

NeuroDebian

NITRC-listed