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
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)|
|Deposited By:||Liza Porijo|
|Deposited On:||30 Aug 2012 04:15|
|Last Modified:||08 Feb 2017 00:17|
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