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Wavelet Kernel Principal Component Analysis in Noisy Multiscale Data Classification
Joint Authors
Lio, Pietro
Krishnan, Sridhar
Lawniczak, Anna T.
Xie, Shengkun
Source
ISRN Computational Mathematics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-07-29
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
We introduce multiscale wavelet kernels to kernel principal component analysis (KPCA) to narrow down the search of parameters required in the calculation of a kernel matrix.
This new methodology incorporates multiscale methods into KPCA for transforming multiscale data.
In order to illustrate application of our proposed method and to investigate the robustness of the wavelet kernel in KPCA under different levels of the signal to noise ratio and different types of wavelet kernel, we study a set of two-class clustered simulation data.
We show that WKPCA is an effective feature extraction method for transforming a variety of multidimensional clustered data into data with a higher level of linearity among the data attributes.
That brings an improvement in the accuracy of simple linear classifiers.
Based on the analysis of the simulation data sets, we observe that multiscale translation invariant wavelet kernels for KPCA has an enhanced performance in feature extraction.
The application of the proposed method to real data is also addressed.
American Psychological Association (APA)
Xie, Shengkun& Lawniczak, Anna T.& Krishnan, Sridhar& Lio, Pietro. 2012. Wavelet Kernel Principal Component Analysis in Noisy Multiscale Data Classification. ISRN Computational Mathematics،Vol. 2012, no. 2012, pp.1-13.
https://search.emarefa.net/detail/BIM-453783
Modern Language Association (MLA)
Xie, Shengkun…[et al.]. Wavelet Kernel Principal Component Analysis in Noisy Multiscale Data Classification. ISRN Computational Mathematics No. 2012 (2012), pp.1-13.
https://search.emarefa.net/detail/BIM-453783
American Medical Association (AMA)
Xie, Shengkun& Lawniczak, Anna T.& Krishnan, Sridhar& Lio, Pietro. Wavelet Kernel Principal Component Analysis in Noisy Multiscale Data Classification. ISRN Computational Mathematics. 2012. Vol. 2012, no. 2012, pp.1-13.
https://search.emarefa.net/detail/BIM-453783
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-453783