Clustering Via Supervised Support Vector Machines

Clustering Via Supervised Support Vector Machines

An SVM-based clustering algorithm is introduced that clusters data with no a priori knowledge of input classes. The algorithm initializes by first running a binary SVM classifier against a data set with each vector in the set randomly labeled. Once this initialization step is complete, the SVM co...

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Bibliographic Details
Main Author: Merat, Sepehr
Format: Others
Published: ScholarWorks@UNO 2008
Subjects:
clustering
machine learning
pattern recognition
support vector machines
supervised learning
unsupervised learning
Online Access:http://scholarworks.uno.edu/td/857
http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=1837&context=td

Internet

http://scholarworks.uno.edu/td/857
http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=1837&context=td

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