Incremental Approach to Classification Learning

Author:

Naidenova Xenia Alexandre1

Affiliation:

1. Research Centre of Military Medical Academy – Saint Petersburg, Russia

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.

Publisher

IGI Global

Reference32 articles.

1. Asha, P., Jebara, T., & Saranya, G. (2014). A Survey on efficient incremental algorithm for mining high utility itemsets in distributive and dynamic database. International Journal of Emerging Technology and Advanced Engineering, 4(1), 146-149.

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