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Title:Towards Accurate and Efficient Classification: A Discriminative and Frequent Pattern-Based Approach
Author(s):Cheng, Hong
Doctoral Committee Chair(s):Han, Jiawei
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Computer Science
Abstract:In conclusion, the framework of discriminative frequent pattern-based classification could lead to a highly accurate, efficient and interpretable classifier on complex data. The pattern-based classification technique would have great impact in a wide range of applications including text categorization, chemical compound classification, software behavior analysis and so on.
Issue Date:2008
Type:Text
Language:English
Description:101 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008.
URI:http://hdl.handle.net/2142/81825
Other Identifier(s):(MiAaPQ)AAI3337732
Date Available in IDEALS:2015-09-25
Date Deposited:2008


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