mvpa2.measures.ireliefΒΆ

FeaturewiseMeasure performing multivariate Iterative RELIEF (I-RELIEF) algorithm. See : Y. Sun, Iterative RELIEF for Feature Weighting: Algorithms, Theories, and Applications, IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), vol. 29, no. 6, pp. 1035-1051, June 2007.

Inheritance diagram of mvpa2.measures.irelief

Functions

pnorm_w(data1[, data2, weight, p]) Weighted p-norm between two datasets (scipy.weave implementation)

Classes

Dataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
ExponentialKernel(*args, **kwargs) The Exponential kernel class.
FeaturewiseMeasure(**kwargs[, null_dist]) A per-feature-measure computed from a Dataset (base class).
IterativeRelief(**kwargs[, threshold, ...]) FeaturewiseMeasure that performs multivariate I-RELIEF
IterativeReliefOnline(**kwargs[, a, ...]) FeaturewiseMeasure that performs multivariate I-RELIEF
IterativeReliefOnline_Devel(**kwargs[, a, ...]) FeaturewiseMeasure that performs multivariate I-RELIEF
IterativeRelief_Devel(**kwargs[, threshold, ...]) FeaturewiseMeasure that performs multivariate I-RELIEF

NeuroDebian

NITRC-listed