A hybrid classification method of k nearest neighbor, Bayesian methods and genetic algorithm

ACI M., Inan C., AVCI M.

EXPERT SYSTEMS WITH APPLICATIONS, vol.37, no.7, pp.5061-5067, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 7
  • Publication Date: 2010
  • Doi Number: 10.1016/j.eswa.2009.12.004
  • Journal Name: EXPERT SYSTEMS WITH APPLICATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.5061-5067
  • Keywords: k Nearest neighbor method, Bayesian method, Genetic algorithm, Hybrid method, Classification, Clustering, SEGMENTATION
  • Çukurova University Affiliated: Yes

Abstract

k Nearest neighbor, Bayesian methods and genetic algorithms are effective methods of machine learning. In this work a hybrid method is formed by using these methods and algorithm together. The aim is to achieve successful results on classifying by eliminating data that make difficult to learn. Forming new data set approach is proposed according to good data on the hand. Test process is done with five of UCI machine learning datasets. These are iris, breast cancer, glass, yeast and wine data sets. Test results are investigated in collaboration with the previous works, and the success of the study is considered. (C) 2009 Elsevier Ltd. All rights reserved.