Multivariate Pattern Analysis in Python

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# mvpa2.datasets.formats

I/O helpers for some commonly used formats for datasets.

Functions

`from_lightsvm_format`(in_[, targets_attr, am]) | Loads dataset from a file in lightsvm format :Parameters: in_ : Anything we could iterate over and obtain strings, such as `File` targets_attr : string, optional Name of the samples attribute to be used to store targets/labels am : `AttributeMap` or None, optional Which mapping to use for mapping labels back into possibly a literal representation.
`to_lightsvm_format`(dataset, out[, ...]) | Export dataset into LightSVM format :Parameters: dataset : Dataset out : Anything understanding .write(string), such as `File` targets_attr : string, optional Name of the samples attribute to be output domain : {None, ‘regression’, ‘binary’, ‘multiclass’}, optional What domain dataset belongs to.

Classes

`AttributeMap`([map, mapnumeric, ...]) | Map to translate literal values to numeric ones (and back).
`Dataset`(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes.

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