Universiti Teknologi Malaysia Institutional Repository

Statistical learning theory and support vector machines

Yuhaniz, Siti Sophiayati and Haron, Habibollah and Nasien, Dewi (2010) Statistical learning theory and support vector machines. In: 2nd International Conference on Computer Research and Development, ICCRD 2010, 7-10 Mei 2010, Kuala Lumpur, Malaysia.

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Official URL: http://dx.doi.org/10.1109/ICCRD.2010.183

Abstract

It has been more than 30 years that statistical learning theory (SLT) has been introduced in the field of machine learning. Its objective is to provide a framework for studying the problem of inference that is of gaining knowledge, making predictions, making decisions or constructing models from a set of data. Support Vector Machine, a method based on SLT, then emerged and becoming a widely accepted method for solving real-world problems. This paper overviews the pattern recognition techniques and describes the state of art in SVM in the field of pattern recognition.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:pattern recognition, statistical learning, support vector machine
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System (Formerly known)
ID Code:28010
Deposited By: Liza Porijo
Deposited On:30 Aug 2012 04:15
Last Modified:25 Sep 2012 08:31

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