NDLI: A fusion approach based on wrapper and filter feature selection methods using majority vote and feature weighting

Content Provider	IEEE Xplore Digital Library
Author	Bouaguel, W. Bel Mufti, G. Limam, M.
Copyright Year	2013
Description	Author affiliation: LARODEC ESSEC, Univ. of Tunis, Tunis, Tunisia (Bel Mufti, G.; Limam, M.) \|\| LARODEC ISGT, Univ. of Tunis, Tunis, Tunisia (Bouaguel, W.)
Abstract	An essential issue in machine learning is identifying a representative features set that serve to construct robust classification models for a particular task. This paper addresses the problem of feature selection for credit scoring. Many feature selection methods were proposed in the past few years to construct accurate credit scoring model. Instead of using a single feature selection method, we propose a new fusion approach that utilizes a number of diverse feature selection methods to do the job. Many approaches have been proposed to build such accurate credit model, of which filters and wrappers were the most popular. A fusion of this two approaches, is thoroughly investigated in this work and several comparisons are carried out to compare the proposed fusion method with the individual approaches. Evaluations on two credit datasets show that feature subsets selected by the fusion method improves classification accuracy.
Sponsorship	Dar Al-Uloom Univ.
Starting Page	1
Ending Page	6
File Size	351373
Page Count	6
File Format	PDF
ISBN	9781467352840
e-ISBN	9781467352857
DOI	10.1109/ICCAT.2013.6522003
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-20
Publisher Place	Tunisia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Wrapper Accuracy Correlation Computational modeling Area measurement Educational institutions Filter fusion Majority vote Information theory
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

A leave-one-feature-out wrapper method for feature selection in data classification

On the effect of search strategies on Wrapper feature selection in credit scoring

A Hybrid Feature Selection Mechanism

An efficient approach for microarray data classification using filter wrapper hybrid approach

Feature Selection and Combination for Stress Identification Using Correlation and Diversity

Feature selection based on particle swarm optimal with multiple evolutionary strategies

Subjectivity detection based on multi-feature fusion

Stability of Filter- and Wrapper-Based Feature Subset Selection

Prediction of hepatitis prognosis using Support Vector Machines and Wrapper Method

A fusion approach based on wrapper and filter feature selection methods using majority vote and feature weighting

Similar Documents

A leave-one-feature-out wrapper method for feature selection in data classification

On the effect of search strategies on Wrapper feature selection in credit scoring

A Hybrid Feature Selection Mechanism

An efficient approach for microarray data classification using filter wrapper hybrid approach

Feature Selection and Combination for Stress Identification Using Correlation and Diversity

Feature selection based on particle swarm optimal with multiple evolutionary strategies

Subjectivity detection based on multi-feature fusion

Stability of Filter- and Wrapper-Based Feature Subset Selection

Prediction of hepatitis prognosis using Support Vector Machines and Wrapper Method

A fusion approach based on wrapper and filter feature selection methods using majority vote and feature weighting