Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/175541
Title: An Integrated Method for Feature Selection Using Fuzzy Information Measure
Researcher: Azhagusundari B.
Guide(s): Antony Selvadoss Thanamani
Keywords: Fuzzy Information
University: Mother Teresa Womens University
Completed Date: 25.11.2016
Abstract: Information overload has been experienced due to advancements in data collection and storage capabilities during the past years. A challenge in highdimensional datasets has bound to give rise to new theoretical developments. One of the issues with high-dimensional datasets is that, not all the measured variables are important for understanding the underlying phenomena of interest. newline
Pagination: viii, 214p.
URI: http://hdl.handle.net/10603/175541
Appears in Departments:Department of Computer Science

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02_certificate.pdf725.28 kBAdobe PDFView/Open
03_abstract.pdf65.68 kBAdobe PDFView/Open
04_declaration.pdf695.73 kBAdobe PDFView/Open
05_acknowledgement.pdf56.48 kBAdobe PDFView/Open
06_contents.pdf35.37 kBAdobe PDFView/Open
07_list of tables.pdf33.49 kBAdobe PDFView/Open
08_list of figures.pdf32.88 kBAdobe PDFView/Open
09_list of abbreviations.pdf31.97 kBAdobe PDFView/Open
10_chapter1.pdf565.67 kBAdobe PDFView/Open
11_chapter2.pdf491.85 kBAdobe PDFView/Open
12_chapter3.pdf251.69 kBAdobe PDFView/Open
13_chapter4.pdf398.56 kBAdobe PDFView/Open
14_chapter5.pdf238.58 kBAdobe PDFView/Open
15_chapter6.pdf64.31 kBAdobe PDFView/Open
16_bibliography.pdf123.89 kBAdobe PDFView/Open
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