Support vector machine and its applications in information processing

With increasing amounts of data being generated by businesses and researchers there is a need for fast, accurate and robust algorithms for data analysis. Improvements in databases technology, computing performance and artificial intelligence have contributed to the development of intelligent data analysis. The primary aim of data mining is to discover patterns in the data that lead to better understanding of the data generating process and to useful predictions. One recent technique that has been developed to handle the ever-increasing complexity of hidden patterns is the support vector machine. The support vector machine has been developed as robust tool for classification and regression in noisy, complex domains. Current thesis work is aimed to explore the area of support vector machine to see the interesting applications in data analysis, especially from the point of view of information processing.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2004

Author dc:creator

• Saxena, Vishal, 1979-

Advisor dc:contributor.advisor

• John R. Williams.

• Civil and Environmental Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/29404

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/29404