Support vector machine and its applications in information processing
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2005
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| Online Access: | http://hdl.handle.net/1721.1/29404 |
| _version_ | 1826199167746179072 |
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| author | Saxena, Vishal, 1979- |
| author2 | John R. Williams. |
| author_facet | John R. Williams. Saxena, Vishal, 1979- |
| author_sort | Saxena, Vishal, 1979- |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004. |
| first_indexed | 2024-09-23T11:15:48Z |
| format | Thesis |
| id | mit-1721.1/29404 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:15:48Z |
| publishDate | 2005 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/294042019-04-11T03:19:09Z Support vector machine and its applications in information processing Saxena, Vishal, 1979- John R. Williams. Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering. Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering. Civil and Environmental Engineering. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2004. Includes bibliographical references (leaves 59-61). 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. by Vishal Saxena. M.Eng. 2005-10-14T20:21:50Z 2005-10-14T20:21:50Z 2004 2004 Thesis http://hdl.handle.net/1721.1/29404 56133040 eng 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. http://dspace.mit.edu/handle/1721.1/7582 72 leaves 2368620 bytes 2368427 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology |
| spellingShingle | Civil and Environmental Engineering. Saxena, Vishal, 1979- Support vector machine and its applications in information processing |
| title | Support vector machine and its applications in information processing |
| title_full | Support vector machine and its applications in information processing |
| title_fullStr | Support vector machine and its applications in information processing |
| title_full_unstemmed | Support vector machine and its applications in information processing |
| title_short | Support vector machine and its applications in information processing |
| title_sort | support vector machine and its applications in information processing |
| topic | Civil and Environmental Engineering. |
| url | http://hdl.handle.net/1721.1/29404 |
| work_keys_str_mv | AT saxenavishal1979 supportvectormachineanditsapplicationsininformationprocessing |