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Deficient data classification with fuzzy learning

Liu, Shigang 2017, Deficient data classification with fuzzy learning, PhD thesis, School of Information Technology, Deakin University.

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Title Deficient data classification with fuzzy learning
Author Liu, Shigang
Institution Deakin University
School School of Information Technology
Faculty Faculty of Science, Engineering and Built Environment
Degree type Research doctorate
Degree name PhD
Thesis advisor Xiang, YangORCID iD for Xiang, Yang orcid.org/0000-0001-5252-0831
Zhang, JunORCID iD for Zhang, Jun orcid.org/0000-0002-2189-7801
Date submitted 2017-02
Keyword(s) machine learning
sampling
imbalanced data
missing data
social networks
adversary learning
Summary This thesis first proposes a novel algorithm for handling both missing values and imbalanced data classification problems. Then, algorithms for addressing the class imbalance problem in Twitter spam detection (Network Security Problem) have been proposed. Finally, the security profile of SVM against deliberate attacks has been simulated and analysed.
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 810199 Defence not elsewhere classified
Description of original xviii, 199 pages : tables, graphs, some coloured
Copyright notice ┬ęThe author. All Rights Reserved.
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30102819

Document type: Thesis
Collections: Higher degree theses (Open Access)
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Created: Thu, 28 Sep 2017, 14:25:43 EST by Asif, Yasmin

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.