Incremental Approach to Classification Learning

View Sample PDF

Author(s): Xenia Alexandre Naidenova (Research Centre of Military Medical Academy – Saint Petersburg, Russia)
Copyright: 2019
Pages: 13
Source title: Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7368-5.ch010

Keywords: Artificial Intelligence / Engineering Science Reference / Human-Computer Interaction / Social Sciences & Humanities

Purchase

View Incremental Approach to Classification Learning on the publisher's website for pricing and purchasing information.

Abstract

An approach to incremental classification learning is proposed. Classification learning is based on approximation of a given partitioning of objects into disjointed blocks in multivalued space of attributes. Good approximation is defined in the form of good maximally redundant classification test or good formal concept. A concept of classification context is introduced. Four situations of incremental modification of classification context are considered: adding and deleting objects and adding and deleting values of attributes. Algorithms of changing good concepts in these incremental situations are given and proven.

The IRMA Community

Research IRM

Incremental Approach to Classification Learning

Purchase

Abstract

Related Content

IRMA Sponsors