Dymitr Ruta, Bogdan Gabrys  Home/Search
Context Related
| cis.paisley.ac.uk/rutaci0...paper3.pdf Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: cis.paisley.ac.uk/...publications (more) (Enter author homepages) |
Rate this article:      (best)Comment on this article |
Abstract: Combining classifiers by majority voting (MV) has recently emerged as an effective way of improving performance of individual classifiers. However, the usefulness of applying MV is not always observed and is subject to distribution of classification outputs in a multiple classifier system (MCS). Evaluation of MV errors (MVE) for all combinations of classifiers in MCS is a complex process of exponential complexity. Reduction of this complexity can be achieved provided the explicit relationship... (Update)
Similar documents based on text: More All
0.8: New Measure of Classifier Dependency in Multiple Classifier.. - Ruta, Gabrys (2002) (Correct)
0.7: A Theoretical Analysis of the Limits of Majority Voting Errors .. - Ruta, Gabrys (2000) (Correct)
0.6: Application of the Evolutionary Algorithms for Classifier.. - Ruta, Gabrys (2001) (Correct)
BibTeX entry: (Update)
Ruta D., Gabrys B.: Analysis of the Correlation Between Majority Voting Errors and the Diversity Measures in Multiple Classifier Systems. Accepted for the International Sympo- sium on Soft Computing SOCO'2001 http://citeseer.ist.psu.edu/ruta01analysis.html More
@misc{ ruta01analysis,
author = "D. Ruta and B. Gabrys",
title = "Analysis of the Correlation Between Majority Voting Errors and the Diversity
Measures in Multiple Classifier Systems",
text = "Ruta D., Gabrys B.: Analysis of the Correlation Between Majority Voting
Errors and the Diversity Measures in Multiple Classifier Systems. Accepted
for the International Sympo- sium on Soft Computing SOCO'2001",
year = "2001",
url = "citeseer.ist.psu.edu/ruta01analysis.html" }
Citations (may not include all citations):133 Methods of combining multiple classifiers and their applicat.. (context) - Xu, Krzyzak - 1992
80 Bias plus variance decomposition for zero-one loss function - Kohavi - 1996
76 IEEE Transactions on Pattern Analysis and Machine Intelligen.. (context) - Hansen, Salamon - 1990
67 Combining the results of several neural network classifiers (context) - Rogova - 1994
61 Error correlation and error reduction in ensemble classifier.. - Tumer, Ghosh - 1996
60 Democracy in neural nets: voting schemes for classification (context) - Battiti - 1994
50 Optimal linear combinations of neural networks - Hashem - 1997
50 Statistical methods for rates and proportions (context) - JL - 1981
35 Fuzzy models and algorithms for pattern recognition and imag.. (context) - JC - 1999
33 Application of majority voting to pattern recognition: an an.. (context) - Lam - 1997
28 Combining artificial neural nets: ensemble and modular multi.. (context) - AJC - 1999
23 Combining forecasts -- twenty years later (context) - CWJ - 1989
17 Measures of diversity in classifier ensembles - LI, CJ
17 A theoretical analysis of the application of majority voting.. (context) - Lam - 1994
16 Combining multiple neural networks by fuzzy integral for rob.. (context) - SB, JH - 1995
[Article contains additional citations not shown here]
Documents on the same site (http://cis.paisley.ac.uk/ruta-ci0/publications.htm): More
Application of the Evolutionary Algorithms for Classifier.. - Ruta, Gabrys (2001) (Correct)
The Boundaries of Knowledge - Ruta, Gabrys (Correct)
Multilayer Selection-Fusion Model for Pattern Classification - Ruta (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC