NDLI: A neuro-fuzzy approach for feature selection

Content Provider	IEEE Xplore Digital Library
Author	Benitez, J.M. Castro, J.L. Mantas, C.J. Rojas, F.
Copyright Year	2001
Description	Author affiliation: Dept. Comput. Sci. & Artificial Intelligence, Granada Univ., Spain (Benitez, J.M.)
Abstract	A method for feature selection based on a combination of artificial neural network and fuzzy techniques is presented. The procedure produces a ranking of features according to their relevance to the network. This ranking is used to perform a backward selection by successively removing input nodes in a network trained using the complete set of features as inputs. Irrelevant input units and their connections are pruned. The remaining biases are adjusted in such a way that the overall change in the behavior learnt by the network is under control. When the problem is too hard to be modeled by a single network, several of them are used to generate different rankings which are aggregated by using a fuzzy logic operator. The proposed method is applied on a number of real-world classification problems. Empirical results show that the feature selection enables the network to improve its generalization ability. This procedure also offers several advantages with respect to other feature selection methods, especially improved efficiency.
Sponsorship	Int. Fuzzy Syst. Assoc.
Starting Page	1003
Ending Page	1008
File Size	498161
Page Count	6
File Format	PDF
ISBN	0780370783
DOI	10.1109/NAFIPS.2001.944742
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-25
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Feature extraction Fuzzy logic Computer science Artificial intelligence Fuzzy neural networks System identification Pattern recognition Neural networks Costs
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

Unsupervised feature evaluation: a neuro-fuzzy approach

Unsupervised neuro-fuzzy feature selection

Feature selection: a neuro-fuzzy approach

Neuro-Fuzzy approach in the recognition of Arabic Characters

Unsupervised feature selection using a fuzzy-genetic algorithm

A physiological neuro fuzzy learning algorithm for medical image recognition

Computational intelligence for structure preserving dimensionality reduction and feature analysis

A survey on feature extraction for pattern recognition

A face recognition system using fuzzy logic and artificial neural network

A neuro-fuzzy approach for feature selection

Similar Documents

Unsupervised feature evaluation: a neuro-fuzzy approach

Unsupervised neuro-fuzzy feature selection

Feature selection: a neuro-fuzzy approach

Neuro-Fuzzy approach in the recognition of Arabic Characters

Unsupervised feature selection using a fuzzy-genetic algorithm

A physiological neuro fuzzy learning algorithm for medical image recognition

Computational intelligence for structure preserving dimensionality reduction and feature analysis

A survey on feature extraction for pattern recognition

A face recognition system using fuzzy logic and artificial neural network

A neuro-fuzzy approach for feature selection