Improving Nearest Neighbor Classification by Elimination of Noisy Irrelevant Features

被引：0

作者：

Zomorodian, M. Javad ^{[1
,2
]}

Adeli, Ali ^{[2
]}

Sinaee, Mehrnoosh ^{[2
]}

Hashemi, Sattar ^{[2
]}

机构：

[1] Shiraz Bahonar Tech Coll, Inst Comp Sci, Shiraz, Iran

[2] Shiraz Univ, Dept Comp Sci & Engn, Shiraz, Iran

来源：

INTELLIGENT INFORMATION AND DATABASE SYSTEMS (ACIIDS 2012), PT II | 2012年 / 7197卷

关键词：

AUC; Genetic algorithm; Feature selection; Noisy feature elimination; k-NN; FEATURE-SELECTION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces the use of GA with a novel fitness function to eliminate noisy and irrelevant features. Fitness function of GA is based on the Area Under the receiver operating characteristics Curve (AUC). The aim of this feature selection is to improve the performance of k-NN algorithm. Experimental results show that the proposed method can substantially improve the classification performance of k-NN algorithm in comparison with the other classifiers (in the realm of feature selection) such as C4.5, SVM, and Relief. Furthermore, this method is able to eliminate the noisy irrelevant features from the synthetic data sets.

引用

页码：11 / 21

页数：11

共 50 条

[1] Noisy data elimination using mutual k-nearest neighbor for classification mining
Liu, Huawen
Zhang, Shichao
[J]. JOURNAL OF SYSTEMS AND SOFTWARE, 2012, 85 (05) : 1067 - 1074
[2] Improving nearest neighbor classification with cam weighted distance
Zhou, CY
Chen, YQ
[J]. PATTERN RECOGNITION, 2006, 39 (04) : 635 - 645
[3] Improving Nearest Neighbor classification with simulated gravitational collapse
Wang, C
Chen, YQ
[J]. ADVANCES IN NATURAL COMPUTATION, PT 3, PROCEEDINGS, 2005, 3612 : 845 - 854
[4] Survey of improving k-nearest-neighbor for classification
Jiang, Liangxiao
Cai, Zhihua
Wang, Dianhong
Jiang, Siwei
[J]. FOURTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 1, PROCEEDINGS, 2007, : 679 - 683
[5] Improving K-Nearest Neighbor Efficacy for FarsiText Classification
Elahimanesh, Mohammad Hossein
BehrouzMinaei-Bidgoli
Malekinezhad, Hossein
[J]. LREC 2012 - EIGHTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION, 2012, : 1618 - 1621
[6] Improving Fusion of Dimensionality Reduction Methods for Nearest Neighbor Classification
Deegalla, Sampath
Bostrom, Henrik
[J]. EIGHTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS, 2009, : 771 - 775
[7] Improving k Nearest Neighbor with Exemplar Generalization for Imbalanced Classification
Li, Yuxuan
Zhang, Xiuzhen
[J]. ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PT II: 15TH PACIFIC-ASIA CONFERENCE, PAKDD 2011, 2011, 6635 : 321 - 332
[8] Simultaneous selection of features and metric for optimal nearest neighbor classification
Johannsen, DA
Wegman, EJ
Solka, JL
Priebe, CE
[J]. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2004, 33 (09) : 2137 - 2157
[9] Improving the Behavior of the Nearest Neighbor Classifier against Noisy Data with Feature Weighting Schemes
Saez, Jose A.
Derrac, Joaquin
Luengo, Julian
Herrera, Francisco
[J]. HYBRID ARTIFICIAL INTELLIGENCE SYSTEMS, HAIS 2014, 2014, 8480 : 597 - 606
[10] Soft nearest neighbor classification
Baram, Y
[J]. 1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, 1997, : 1469 - 1473

← 1 2 3 4 5 →