Year: 2019
Type: conference-paper
Abstract: At present the most popular criteria are of informative heuristic criteria associated with the estimation of separability given classes and based on the fundamental pattern recognition compactness hypothesis: with increasing distance between the classes improved their separability. “Good” are those features that maximize the relationship. Such heuristic criteria, although are widely used in solving practical problems of classification, but in theory are scarcely explored. At present, the method of selecting informative features, taking into account the relationships of features based on heuristic criteria, has not been developed. The report considers this task.
Authors: N Mamatov, A Samijonov, Z Yuldashev
Institution: Bauman Moscow State Technical University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2972699208