Pattern classification via unsupervised learners
We consider classification problems in a variant of the Probably Approximately Correct (PAC)-learning framework, in which an unsupervised learner creates a discriminant function over each class and observations are labeled by the learner returning the highest value associated with that observation....
Main Author: | Palmer, Nicholas James |
---|---|
Published: |
University of Warwick
2008
|
Subjects: | |
Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491521 |
Similar Items
-
An investigation of multilevel refinement in routing and location problems
by: Rodney, Demane O'Neil
Published: (2008) -
A speech recognition system using Walsh analysis with a small computer
by: Abu El-Ata, Monira
Published: (1980) -
The development of 'for experts systems' as heuristic reasoning platforms in risk decision support : a consideration of tool design, technology transfer and compatability with Bayesian decision analysis
by: Arthur, J. G.
Published: (2007) -
Strategy iteration algorithms for games and Markov decision processes
by: Fearnley, John
Published: (2010) -
Novel fuzzy techniques for modelling human decision making
by: Musikasuwan, Salang
Published: (2013)