Discriminative learning for minimum error classification (pattern recognition)
- 1 December 1992
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Signal Processing
- Vol. 40 (12) , 3043-3054
- https://doi.org/10.1109/78.175747
Abstract
A formulation is proposed for minimum-error classification, in which the misclassification probability is to be minimized based on a given set of training samples. A fundamental technique for designing a classifier that approaches the objective of minimum classification error in a more direct manner than traditional methods is given. The method is contrasted with several traditional classifier designs in typical experiments to demonstrate the superiority of the new learning formulation. The method can applied to other classifier structures as well. Experimental results pertaining to a speech recognition task are provided to show the effectiveness of the technique.<>Keywords
This publication has 14 references indexed in Scilit:
- Discriminative multi-layer feed-forward networksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- New discriminative training algorithms based on the generalized probabilistic descent methodPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- On the approximate realization of continuous mappings by neural networksNeural Networks, 1989
- On the use of bandpass liftering in speech recognitionIEEE Transactions on Acoustics, Speech, and Signal Processing, 1987
- An introduction to computing with neural netsIEEE ASSP Magazine, 1987
- A Theory of Adaptive Pattern ClassifiersIEEE Transactions on Electronic Computers, 1967
- An Adaptive Pattern Classification SystemIEEE Transactions on Systems Science and Cybernetics, 1966
- An Algorithm for Linear Inequalities and its ApplicationsIEEE Transactions on Electronic Computers, 1965
- The Relaxation Method for Linear InequalitiesCanadian Journal of Mathematics, 1954
- THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMSAnnals of Eugenics, 1936