To provide the most recent news and documentation www.pymvpa.org reflects the development 2.0 series (renamed 0.6 series) of PyMVPA. If you are interested in the documentation of the previous stable 0.4 series of PyMVPA, please visit v04.pymvpa.org.

mvpa2.clfs.transerror.chisquare

mvpa2.clfs.transerror.chisquare(obs, exp='uniform')

Compute the chisquare value of a contingency table with arbitrary dimensions.

Parameters :

obs : array

Observations matrix

exp : (‘uniform’, ‘indep_rows’) or array, optional

Matrix of expected values of the same size as obs. If no array is given, then for ‘uniform’ – evenly distributes all observations. In ‘indep_rows’ case contingency table takes into account frequencies relative across different columns, so, if the contingency table is predictions vs targets, it would account for dis-balance among different targets. Although ‘uniform’ is the default, for confusion matrices ‘indep_rows’ is preferable.

Returns :

tuple :

chisquare-stats, associated p-value (upper tail)

NeuroDebian

NITRC-listed