Support vector machine and its applications in information processing
Author(s)
Saxena, Vishal, 1979-
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Other Contributors
Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.
Advisor
John R. Williams.
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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.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004. Includes bibliographical references (leaves 59-61).
Date issued
2004Department
Massachusetts Institute of Technology. Department of Civil and Environmental EngineeringPublisher
Massachusetts Institute of Technology
Keywords
Civil and Environmental Engineering.