NDLI: Uncertainty Estimation Using Fuzzy Measures for Multiclass Classification

Content Provider	IEEE Xplore Digital Library
Author	Graves, K.E. Nagarajah, R.
Copyright Year	1990
Abstract	Uncertainty arises in classification problems when the input pattern is not perfect or measurement error is unavoidable. In many applications, it would be beneficial to obtain an estimate of the uncertainty associated with a new observation and its membership within a particular class. Although statistical classification techniques base decision boundaries according to the probability distributions of the patterns belonging to each class, they are poor at supplying uncertainty information for new observations. Previous research has documented a multiarchitecture, monotonic function neural network model for the representation of uncertainty associated with a new observation for two-class classification. This paper proposes a modification to the monotonic function model to estimate the uncertainty associated with a new observation for multiclass classification. The model, therefore, overcomes a limitation of traditional classifiers that base decisions on sharp classification boundaries. As such, it is believed that this method will have advantages for applications such as biometric recognition in which the estimation of classification uncertainty is an important issue. This approach is based on the transformation of the input pattern vector relative to each classification class. Separate, monotonic, single-output neural networks are then used to represent the "degree-of-similarity" between each input pattern vector and each class. An algorithm for the implementation of this approach is proposed and tested with publicly available face-recognition data sets. The results indicate that the suggested approach provides similar classification performance to conventional principle component analysis (PCA) and linear discriminant analysis (LDA) techniques for multiclass pattern recognition problems as well as providing uncertainty information caused by misclassification
Sponsorship	IEEE Computational Intelligence Society
Page Count	13
File Size	1783188
Starting Page	128
Ending Page	140
File Format	PDF
ISSN	10459227
Volume Number	18
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Neural networks Linear discriminant analysis Measurement errors Probability distribution Biometrics Vectors Testing Information analysis Pattern analysis uncertainty estimation Monotonicity neural-network possibility theory
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

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

Study on feature weight and feature selection in pattern classification neural networks

Topology constraint free fuzzy gated neural networks for pattern recognition

Discriminant Analysis for Fast Multiclass Data Classification Through Regularized Kernel Function Approximation

Classification of Heartbeats based on Linear Discriminant Analysis and Artificial Neural Network

Adaptive probabilistic neural networks for pattern classification in time-varying environment

Multiclass Posterior Probability Support Vector Machines

A minimum error approach to speech and pattern recognition

Feature extraction using fuzzy complete linear discriminant analysis

Intelligent Visual Recognition and Classification of Cork Tiles With Neural Networks

Uncertainty Estimation Using Fuzzy Measures for Multiclass Classification

Similar Documents

Study on feature weight and feature selection in pattern classification neural networks

Topology constraint free fuzzy gated neural networks for pattern recognition

Discriminant Analysis for Fast Multiclass Data Classification Through Regularized Kernel Function Approximation

Classification of Heartbeats based on Linear Discriminant Analysis and Artificial Neural Network

Adaptive probabilistic neural networks for pattern classification in time-varying environment

Multiclass Posterior Probability Support Vector Machines

A minimum error approach to speech and pattern recognition

Feature extraction using fuzzy complete linear discriminant analysis

Intelligent Visual Recognition and Classification of Cork Tiles With Neural Networks

Uncertainty Estimation Using Fuzzy Measures for Multiclass Classification