Estimator for classifier error distributions.

Inheritance diagram of mvpa2.clfs.stats


auto_null_dist(dist) Cheater for human beings – wraps dist if needed with some
match_distribution(data[, nsamples, loc, ...]) Determine best matching distribution.
nanmean(x[, axis]) Compute the mean over the given axis ignoring NaNs.
plot_distribution_matches(data, matches[, ...]) Plot best matching distributions


AdaptiveNormal(dist, **kwargs) Adaptive Normal Distribution: params are (0, sqrt(1/nfeatures))
AdaptiveNullDist(dist, **kwargs) Adaptive distribution which adjusts parameters according to the data
AdaptiveRDist(dist, **kwargs) Adaptive rdist: params are (nfeatures-1, 0, 1)
FixedNullDist(dist, **kwargs) Proxy/Adaptor class for SciPy distributions.
MCNullDist(permutator[, dist_class, measure]) Null-hypothesis distribution is estimated from randomly permuted data labels.
Nonparametric(dist_samples[, correction]) Non-parametric 1d distribution – derives cdf based on stored values.
NullDist([tail]) Base class for null-hypothesis testing.
rv_semifrozen(dist[, loc, scale, args]) Helper proxy-class to fit distribution when some parameters are known