NDLI: Evolving learners’ behavior in data mining

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Evolving learners’ behavior in data mining

Content Provider	Springer Nature Link
Author	Pise, Nitin Kulkarni, Parag
Copyright Year	2016
Abstract	An evaluation and choice of learning algorithms is a current research area in data mining, artificial intelligence and pattern recognition, etc. Supervised learning is one of the tasks most frequently used in data mining. There are several learning algorithms available in machine learning field and new algorithms are being added in machine learning literature. There is a need for selecting the best suitable learning algorithm for a given data. With the information explosion of different learning algorithms and the changing data scenarios, there is a need of smart learning system. The paper shows one approach where past experiences learned are used to suggest the best suitable learner using 3 meta-features namely simple, statistical and information theoretic features. The system tests 38 UCI benchmark datasets from various domains using nine classifiers from various categories. It is observed that for 29 datasets, i.e., 76 % of datasets, both the predicted and actual accuracies directly match. The proposed approach is found to be correct for algorithm selection of these datasets. New proposed equation of finding classifier accuracy based on meta-features is determined and validated. The study compares various supervised learning algorithms by performing tenfold cross-validation paired t test. The work helps in a critical step in data mining for selecting the suitable data mining algorithm.
Starting Page	243
Ending Page	259
Page Count	17
File Format	PDF
ISSN	18686478
Journal	Evolving Systems
Volume Number	8
Issue Number	4
e-ISSN	18686486
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-09-21
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Machine learning Data mining techniques Classification Data characteristics Learning algorithms Intelligent data analysis Complexity Artificial Intelligence (incl. Robotics) Complex Systems
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation Computer Science Applications

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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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