relevance

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

Formal Presentation of User Information With Detection Meaningful Objects

The user activity for finding informative meaningful objects needed to solve the problem is considered. To formalize this activity, set theory is used. The mathematical models of formulation of request, analysis of the issued documents and selection of information objects for the solution to the user problem are presented. In addition, mathematical models of intellectual activitiesof user and cognitive processes are developed. The experimental results of the search engines such as Google, Yandex, META, Rambler, Yahoo are given.