Combination of Classifiers With Optimal Weight Based on Evidential Reasoning

An Evidential Reasoning Approach to Weighted Combination of Classifiers for Word Sense Disambiguation

Arguing that various ways of using context in word sense disambiguation (WSD) can be considered as distinct representations of a polysemous word, a theoretical framework for the weighted combination of soft decisions generated by experts employing these distinct representations is proposed in this paper. Essentially, this approach is based on the Dempster-Shafer theory of evidence. By taking th...

Discounting and Combination Operations in Evidential Reasoning

Evidential reasoning is now a leading topic in Artificial Intelligence. Evidence is repre­ sented by a variety of evidential functions. Evidential reasoning is carried out by cer­ tain kinds of fundamental operation on these functions. This paper discusses two of the basic operations on evidential functions, the discount operation and the well-known or­ thogonal sum operation. We show that the ...

Evidential reasoning rule for evidence combination

Article history: Received 26 January 2013 Received in revised form 9 September 2013 Accepted 13 September 2013 Available online 23 September 2013

Likelihood-based Vs Distance-based Evidential Classifiers

Automatic Sleep Stages Detection Based on EEG Signals Using Combination of Classifiers

Sleep stages classification is one of the most important methods for diagnosis in psychiatry and neurology. In this paper, a combination of three kinds of classifiers are proposed which classify the EEG signal into five sleep stages including Awake, N-REM (non-rapid eye movement) stage 1, N-REM stage 2, N-REM stage 3 and 4 (also called Slow Wave Sleep), and REM. Twenty-five all night recordings...