mvpa2.clfs.meta.NFoldPartitioner

class mvpa2.clfs.meta.NFoldPartitioner(cvtype=1, **kwargs)

Generic N-fold data partitioner.

Given a dataset with N chunks, with cvtype = 1 (which is default), it would generate N partition sets, where each chunk is sequentially taken out (with replacement) to form a second partition, while all other samples together form the first partition. Example, if there are 4 chunks, partition sets for cvtype = 1 are:

[[1, 2, 3], [0]]
[[0, 2, 3], [1]]
[[0, 1, 3], [2]]
[[0, 1, 2], [3]]

If cvtype>1, then all possible combinations of cvtype number of chunks are taken out, so for cvtype = 2 in previous example yields:

[[2, 3], [0, 1]]
[[1, 3], [0, 2]]
[[1, 2], [0, 3]]
[[0, 3], [1, 2]]
[[0, 2], [1, 3]]
[[0, 1], [2, 3]]

Note that the “taken-out” partition is always labeled ‘2’ while the remaining elements are labeled ‘1’.

Notes

Available conditional attributes:

• calling_time+: Time (in seconds) it took to call the node

(Conditional attributes enabled by default suffixed with +)

Parameters :

cvtype : int

Type of leave-one-out scheme: N-(cvtype)

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

count : None or int

Desired number of splits to be output. It is limited by the number of splits possible for a given splitter (e.g. OddEvenSplitter can have only up to 2 splits). If None, all splits are output (default).

selection_strategy : str

If count is not None, possible strategies are possible: ‘first’: First count splits are chosen; ‘random’: Random (without replacement) count splits are chosen; ‘equidistant’: Splits which are equidistant from each other.

attr : str

Sample attribute used to determine splits.

space : str

Name of the to be created sample attribute defining the partitions. In addition, a dataset attribute named ‘space_set’ will be added to each output dataset, indicating the number of the partition set it corresponds to.

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