FISA: Feature-based instance selection for imbalanced text classification

FISA: Feature-based instance selection for imbalanced text classification

Support Vector Machines (SVM) classifiers are widely used in text classification tasks and these tasks often involve imbalanced training. In this paper, we specifically address the cases where negative training documents significantly outnumber the positive ones. A generic algorithm known as FISA (F...

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Bibliographic Details
Main Authors: SUN, Aixin, LIM, Ee Peng, Benatallah, Boualem, Hassan, Mahbub
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2006
Subjects:
Vector support machine
Statistical analysis
Electronic discussion group
Classification
Natural language
Text
Information retrieval
Content analysis
Data analysis
Knowledge discovery
Data mining
Databases and Information Systems
Numerical Analysis and Scientific Computing
Online Access:https://ink.library.smu.edu.sg/sis_research/894
https://ink.library.smu.edu.sg/context/sis_research/article/1893/viewcontent/Sun2006_Chapter_FISAFeature_BasedInstanceSelec.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/894
https://ink.library.smu.edu.sg/context/sis_research/article/1893/viewcontent/Sun2006_Chapter_FISAFeature_BasedInstanceSelec.pdf

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