Statistical analysis of three new measures of relevance redundancy and complementarity
Discriminant analysis is part of statistical learning; its goal is to separate classes defined a priori on a population and involves predicting the class of given data points. Discriminant analysis is applied in various fields such as pattern recognition, DNA microarray etc. In recent years, the discrimination problem remains a challenging task that has received increasing attention, especially for high-dimensional data sets. Indeed, in such a case, the feature selection is necessary, which implies the use of criteria of relevance, redundancy and complementarity of e