mvpa2.clfs.statsΒΆ

Estimator for classifier error distributions.

Inheritance diagram of mvpa2.clfs.stats

Functions

auto_null_dist(dist) Cheater for human beings – wraps dist if needed with some
is_datasetlike(obj) Check if an object looks like a Dataset.
kstest(rvs, cdf[, args, N, alternative, mode]) Perform the Kolmogorov-Smirnov test for goodness of fit.
match_distribution(data[, nsamples, loc, ...]) Determine best matching distribution.
nanmean(x[, axis]) Compute the mean over the given axis ignoring NaNs.

Classes

AdaptiveNormal(dist, **kwargs) Adaptive Normal Distribution: params are (0, sqrt(1/nfeatures)) ..
AdaptiveNullDist(dist, **kwargs) Adaptive distribution which adjusts parameters according to the data WiP: internal implementation might change ..
AdaptiveRDist(dist, **kwargs) Adaptive rdist: params are (nfeatures-1, 0, 1) ..
AttributePermutator(attr[, count, limit, assure]) Node to permute one a more attributes in a dataset.
ClassWithCollections([descr]) Base class for objects which contain any known collection Classes inherited from this class gain ability to access collections and their items as simple attributes.
ConditionalAttribute([enabled]) Simple container intended to conditionally store the value ..
Dataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
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 It is an ugly hack with snippets of code taken from scipy, which is Copyright (c) 2001, 2002 Enthought, Inc.

NeuroDebian

NITRC-listed