Bookcover of Robust Clustering Algorithms and Potential Applications
Booktitle:

Robust Clustering Algorithms and Potential Applications

Algorithms for robust data clustering, image segmentation and data classification

VDM Verlag Dr. Müller (2009-07-19 )

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ISBN-13:

978-3-639-18069-5

ISBN-10:
3639180690
EAN:
9783639180695
Book language:
English
Blurb/Shorttext:
Several novel and robust learning algorithms, with the aim to overcome the drawbacks of traditional clustering algorithms, are developed for data clustering and its applications. The effectiveness and superiority of the proposed methods are supported by experimental results. 1) Te proposed RDA exhibits several robust clustering characteristics: robust to the initialization; robust to cluster volumes; and robust to noise and outliers. 2) The proposed IFCSS algorithm achieves two robust clustering characteristics: the robustness against noisy points is obtained by the maximization of mutual information; and the optimal cluster number is auto-determined by the VC-bound induced cluster validity. 3) The KDA is developed to discover some complicated (e.g., linearly nonseparable) data structures which can not be revealed by traditional clustering methods in the standard Euclidean space. 4) Finally, robust clustering methods have been developed for image segmentation and pattern classification. The proposed ASDA can perform unsupervised clustering for robust image segmentation. The KPCM is developed to generate weights used for SVM training.
Publishing house:
VDM Verlag Dr. Müller
Website:
http://www.vdm-verlag.de
By (author) :
Xu-Lei Yang
Number of pages:
192
Published at:
2009-07-19
Stock:
Available
Category:
Technology
Price:
68.00 €
Keywords:
Robust Clustering Algorithms, Fuzzy Clustering Algorithm, Pattern Classification, Image Segmentation, Kernel Methods, Mutual Informatin Optimization, Statistical Theory., Statistical Theory.

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