Abstract
The feature selection problem as a task of a transformation of an initial pattern space into a new space, optimal with respect to the discriminatory features is described. Transformation optimizations are realized according to the measures which may be included in the broadly understood group of Fisher measures. In particular, the use of some conception of interclass scatter matrix calculation allows us to obtain different variations of many-class Fisher measures. Finally, a theoretical comparison of some properties of the suggested Fisher transformations with other transformations based on the Karhunen-Loève expansion is presented.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
