NDLI: Tackle three practical classification problems via Ensemble Learning

Content Provider	IEEE Xplore Digital Library
Author	Xuzhou Li
Copyright Year	2012
Description	Author affiliation: School of Computer Science & Technology, Shandong University, Jinan, China (Xuzhou Li)
Abstract	News Categorization, Intrusion Detection and Spam Detection are three practical $problems^{1}$ in Data Mining and Cybersecurity. Their focus is on string sequences analysis towards application of knowledge discovery techniques for protecting personal computer information by means of detection, prevention, and response to various attacks. These three string sequences analysis problems could be treated as three classification problems. To tackle these three classifications problems, we propose a Ensemble Learning method. The idea of ensemble learning is to employ multiple learners and combine their predictions. These ensemble methods utilize multiple models to obtain better predictive performance than could be obtained from any of the constituent models[13], [14], [16]. In the tasks, we utilize (LDA-, SK-)SVM, (LDA-, SK-)GP and (LDA-, SK-) AdaBoost as the weak classifiers, and the experiments shows that ensemble learning method can improve the classification performance significantly.
Starting Page	248
Ending Page	252
File Size	856125
Page Count	5
File Format	PDF
ISBN	9781467323109
e-ISBN	9781467323116
DOI	10.1109/GrC.2012.6468566
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Analytical models AdaBoost Support vector machine classification LDA GP SVM Ensemble learning
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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