Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.
Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.
Evaluates the worth of a subset of attributes by the level of consistency in the class values when the training instances are projected onto the subset of attributes.
Abstract attribute subset evaluator capable of evaluating subsets with
respect to a data set that is distinct from that used to initialize/
train the subset evaluator.
Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class.