Title :
Feature-weighted k-Nearest Neighbor Classifier
Author :
Vivencio, Diego P. ; Hruschka, Estevam R., Jr. ; do Carmo Nicoletti, M. ; Santos, Edimilson B dos ; Galvao, Sebastian D C O
Author_Institution :
DC/UFSCar, S. Carlos
Abstract :
This paper proposes a feature weighting method based on X2 statistical test, to be used in conjunction with a k-NN classifier. Results of empirical experiments conducted using data from several knowledge domains are presented and discussed. Forty four out of forty five conducted experiments favoured the feature weighted approach and are empirical evidence that the proposed weighting process based on X2 is a good weighting strategy
Keywords :
pattern classification; statistical analysis; feature weighting method; feature-weighted k-nearest neighbor classifier; k-NN classifier; statistical test; Accuracy; Computational intelligence; Data mining; Machine learning; Machine learning algorithms; Mutual information; Nearest neighbor searches; Neural networks; Testing; Time measurement; Feature Ranking; Feature Selection; Instance-Based Learning;
Conference_Titel :
Foundations of Computational Intelligence, 2007. FOCI 2007. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0703-6
DOI :
10.1109/FOCI.2007.371516
