DocumentCode :
3512942
Title :
Novel feature selection method using mutual information and fractal dimension
Author :
Pham, D.T. ; Packianather, M.S. ; Garcia, M.S. ; Castellani, M.
Author_Institution :
Manuf. Eng. Centre, Cardiff Univ., Cardiff, UK
fYear :
2009
fDate :
3-5 Nov. 2009
Firstpage :
3393
Lastpage :
3398
Abstract :
In this paper, a novel feature selection method using Mutual Information (MI) and Fractal Dimension (FD) to measure the relevance and the redundancy features is presented. The proposed algorithm maximises the relevance and minimises the redundancy of the attributes simultaneously. The new framework allows a more efficient method for the selection of features without using any search technique. The performance of the proposed algorithm is compared with three different feature selection methods on three different datasets. The results obtained confirm the comparable efficiency and effectiveness of the features selected through the proposed algorithm.
Keywords :
learning (artificial intelligence); multilayer perceptrons; feature selection method; fractal dimension; mutual information; search technique; Data analysis; Feedback; Filters; Fractals; Image segmentation; Information analysis; Mutual information; Performance analysis; Pulp manufacturing; Satellites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2009. IECON '09. 35th Annual Conference of IEEE
Conference_Location :
Porto
ISSN :
1553-572X
Print_ISBN :
978-1-4244-4648-3
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2009.5415365
Filename :
5415365
Link To Document :
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