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University of Illinois at Urbana-Champaign
Towards Accurate and Efficient Classification: A Discriminative and Frequent Pattern-Based Approach
Abstract
dc:descriptionIn 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.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Cheng, Hong
- Contributors dc:contributor
-
- Han, Jiawei
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (MiAaPQ)AAI3337732
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/81825