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

doi:10.1109/ICCE-TW.2015.7217050

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

Department of Information Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	96-97
Number of pages	2
ISBN (Electronic)	9781479987443
DOIs	https://doi.org/10.1109/ICCE-TW.2015.7217050
State	Published - 20 Aug 2015
Event	2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015 - Taipei, Taiwan Duration: 6 Jun 2015 → 8 Jun 2015

Publication series

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

Conference

Conference	2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015
Country/Territory	Taiwan
City	Taipei
Period	6/06/15 → 8/06/15

Keywords

Accuracy
Linear programming
Prediction algorithms
Prototypes
Sociology
Statistics
Training

Access to Document

10.1109/ICCE-TW.2015.7217050

Cite this

Chen, J. L., Huang, K. W., Tsai, P. W., & Yang, C. S. (2015). A prototype generation with same class label proportion method for nearest neighborhood classification. In 2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015 (pp. 96-97). [7217050] (2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-TW.2015.7217050

Chen, Jui Le ; Huang, Ko Wei ; Tsai, Pang Wei et al. / A prototype generation with same class label proportion method for nearest neighborhood classification. 2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 96-97 (2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015).

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abstract = "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.",

keywords = "Accuracy, Linear programming, Prediction algorithms, Prototypes, Sociology, Statistics, Training",

author = "Chen, {Jui Le} and Huang, {Ko Wei} and Tsai, {Pang Wei} and Yang, {Chu Sing}",

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Chen, JL, Huang, KW, Tsai, PW & Yang, CS 2015, A prototype generation with same class label proportion method for nearest neighborhood classification. in 2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015., 7217050, 2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015, Institute of Electrical and Electronics Engineers Inc., pp. 96-97, 2nd IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015, Taipei, Taiwan, 6/06/15. https://doi.org/10.1109/ICCE-TW.2015.7217050

A prototype generation with same class label proportion method for nearest neighborhood classification. / Chen, Jui Le; Huang, Ko Wei; Tsai, Pang Wei et al.

2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 96-97 7217050 (2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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KW - Linear programming

KW - Prediction algorithms

KW - Prototypes

KW - Sociology

KW - Statistics

KW - Training

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Chen JL, Huang KW, Tsai PW, Yang CS. A prototype generation with same class label proportion method for nearest neighborhood classification. In 2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 96-97. 7217050. (2015 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2015). doi: 10.1109/ICCE-TW.2015.7217050

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

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