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Author Zhuang, Ling.

Title Reducing performance bias by intrinsically insensitive learning for unbalanced text mining / by Ling Zhuang
Published [Place of publication not identified] : [publisher not identified], 2006


Location Call no. Vol. Availability
 MELB  006.312 Zha/Rpb  AVAILABLE
Description x, 151 pages : illustrations ; 30 cm
Summary This thesis proposes three effective strategies to solve the significant performance-bias problem in imbalance text mining: (1) creation of a novel inexact field learning algorithm to overcome the dual-imbalance problem; (2) introduction of the one-class classification-framework to optimize classifier-parameters, and (3) proposal of a maximal-frequent-item-set discovery approach to achieve higher accuracy and efficiency
Notes Submitted to the School of Engineering and Information Technology of the Faculty of Science and Technology, Deakin University
Degree conferred 2007
Thesis (Ph.D.)--Deakin University, Victoria, 2006
Bibliography Includes bibliographical references (pages 132-147) and index
Subject Data mining.
Genre/Form Academic theses.
Author Deakin University. Faculty of Science and Technology.
Deakin University. School of Engineering and Information Technology