Independent nearest features memory-based classifier

Pateritsas, C; Stafylopatis, A

dc.contributor.author	Pateritsas, C	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T02:43:23Z
dc.date.available	2014-03-01T02:43:23Z
dc.date.issued	2005	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31372
dc.subject	bayesian classifier	en
dc.subject	Data Mining	en
dc.subject	K Nearest Neighbor	en
dc.subject.other	Algorithms	en
dc.subject.other	Data mining	en
dc.subject.other	Feature extraction	en
dc.subject.other	Problem solving	en
dc.subject.other	Bayesian classifiers	en
dc.subject.other	K-nearest-neighbors	en
dc.subject.other	Classification (of information)	en
dc.title	Independent nearest features memory-based classifier	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/CIMCA.2005.1631563	en
heal.identifier.secondary	http://dx.doi.org/10.1109/CIMCA.2005.1631563	en
heal.identifier.secondary	1631563	en
heal.publicationDate	2005	en
heal.abstract	The classification task is one of the most important problems in the area of data mining. In this paper we propose a new algorithm for addressing this problem. The main idea derives from the well-known algorithm of k-nearest-neighbors. In the proposed approach, given an unclassified pattern, a set of neighboring patterns is found, but not necessarily using all input feature dimensions. Also, following the concept of the naive Bayesian classifier, independence of input feature dimensions in the outcome of the classification task is assumed. The two concepts are merged in an attempt to take advantage of their good performance features. Experimental results have shown superior performance of the proposed method in comparison with the aforementioned algorithms and their variations. © 2005 IEEE.	en
heal.journalName	Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet	en
dc.identifier.doi	10.1109/CIMCA.2005.1631563	en
dc.identifier.volume	2	en
dc.identifier.spage	781	en
dc.identifier.epage	786	en