Decision boundary setting and classifier combination for text classification

Bijaksana, Moch Arif (2015) Decision boundary setting and classifier combination for text classification. PhD thesis, Queensland University of Technology.

Abstract

This thesis presents a promising boundary setting method for solving challenging issues in text classification to produce an effective text classifier. A classifier must identify boundary between classes optimally. However, after the features are selected, the boundary is still unclear with regard to mixed positive and negative documents. A classifier combination method to boost effectiveness of the classification model is also presented. The experiments carried out in the study demonstrate that the proposed classifier is promising.

Impact and interest:

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Full-text downloads:

86 since deposited on 13 May 2015
35 in the past twelve months

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ID Code: 82827
Item Type: QUT Thesis (PhD)
Supervisor: Li, Yuefeng & Sitbon, Laurianne
Keywords: Text Classification, Decision Boundary Setting, Pattern Mining, Relevance Feature Discovery, Classifier Combination
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 13 May 2015 04:25
Last Modified: 22 Mar 2016 00:20

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