A prototype generation with same class label proportion method for nearest neighborhood classification

Jui Le Chen, Ko Wei Huang, Pang Wei Tsai, Chu Sing Yang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

The KNN algorithm has a significant effect on classification prediction in Data Mining. In order to solve the drawbacks for KNN algorithm to reduce the costs of the calculation and increase the accuracy, this paper proposed a prototype generation method with same class label proportion for classification to ensure that each class has at least a prototype to be represented. We compare the average success rate of GA, PSO, DE and proposed method SPDE. The experimental results show that the SPDE has more opportunity to do better than others in those problems.

原文???core.languages.en_GB???
主出版物標題2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015
發行者Institute of Electrical and Electronics Engineers Inc.
頁面96-97
頁數2
ISBN(電子)9781479987443
DOIs
出版狀態已出版 - 20 8月 2015
事件2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015 - Taipei, Taiwan
持續時間: 6 6月 20158 6月 2015

出版系列

名字2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015

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???event.eventtypes.event.conference???2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015
國家/地區Taiwan
城市Taipei
期間6/06/158/06/15

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