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.
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 |