| Multivariate Pattern Analysis in Python

### Navigation

- index
- next |
- previous |
- ExpPsy Project |
- NeuroDebian Project |
- PyMVPA 0.4.x Home |
- PyMVPA Home |
- Documentation »
- Full Examples »

This content refers to the previous stable release of PyMVPA. Please visit www.pymvpa.org for the most recent version of PyMVPA and its documentation.

# Tiny Example of a Full Cross-Validation

Very, very simple example showing a complete cross-validation procedure with no fancy additions whatsoever.

    # get PyMVPA running
    from mvpa.suite import *

    # load PyMVPA example dataset
    attr = SampleAttributes(os.path.join(pymvpa_dataroot, 'attributes.txt'))
    dataset = NiftiDataset(samples=os.path.join(pymvpa_dataroot, 'bold.nii.gz'),
                           labels=attr.labels,
                           chunks=attr.chunks,
                           mask=os.path.join(pymvpa_dataroot, 'mask.nii.gz'))

    # do chunkswise linear detrending on dataset
    detrend(dataset, perchunk=True, model='linear')

    # zscore dataset relative to baseline ('rest') mean
    zscore(dataset, perchunk=True, baselinelabels=[0],
           targetdtype='float32')

    # select class 1 and 2 for this demo analysis
    # would work with full datasets (just a little slower)
    dataset = dataset.selectSamples(
                    N.array([l in [1, 2] for l in dataset.labels],
                            dtype='bool'))

    # setup cross validation procedure, using SMLR classifier
    cv = CrossValidatedTransferError(
                TransferError(SMLR()),
                OddEvenSplitter())
    # and run it
    error = cv(dataset)

    print "Error for %i-fold cross-validation on %i-class problem: %f" \
          % (len(dataset.uniquechunks), len(dataset.uniquelabels), error)

See also

The full source code of this example is included in the PyMVPA source distribution (doc/examples/start_easy.py).

### Navigation

- index
- next |
- previous |
- ExpPsy Project |
- NeuroDebian Project |
- PyMVPA 0.4.x Home |
- PyMVPA Home |
- Documentation »
- Full Examples »