Rough Sets and Bayes Factor

2005 ◽  
pp. 202-229 ◽  
Author(s):  
Dominik Ślęzak
Keyword(s):  
Rough Sets ◽  
Bayes Factor

Assessing the Replication Bayes Factor: The Case of Global Versus Local Priming

2014 ◽  
Author(s):  
Sarahanne Field ◽  
Eric-Jan Wagenmakers ◽  
Ben Newell ◽  
Don Van Ravenzwaaij
Keyword(s):  
Bayes Factor

BUSINESS FAILURE PREDICTION USING ROUGH SETS: A COMPARISON WITH MULTIVARIATE ANALYSIS TECHNIQUES

1999 ◽  
Vol 04 (01) ◽  
Author(s):  
C. Zopounidis ◽  
M. Doumpos ◽  
R. Slowinski ◽  
R. Susmaga ◽  
A. I. Dimitras
Keyword(s):  
Multivariate Analysis ◽  
Rough Sets ◽  
Failure Prediction ◽  
Business Failure ◽  
Analysis Techniques

Approximation Sets of Rough Sets

2012 ◽  
Vol 23 (7) ◽  
pp. 1745-1759 ◽  
Author(s):  
Qing-Hua ZHANG ◽  
Guo-Yin WANG ◽  
Yu XIAO
Keyword(s):  
Rough Sets

Analysing diabetes using rough sets

2020 ◽  
pp. 533-538
Author(s):  
S. Arjun Raj ◽  
M. Vigneshwaran
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Rough Set Theory ◽  
International Diabetes Federation ◽  
Published Data ◽  
Lower And Upper Approximations

In this article we use the rough set theory to generate the set of decision concepts in order to solve a medical problem.Based on officially published data by International Diabetes Federation (IDF), rough sets have been used to diagnose Diabetes.The lower and upper approximations of decision concepts and their boundary regions have been formulated here.

Comparação entre Redes Neurais Artificiais e Rough Sets para Classificação de Dados

2016 ◽  
Author(s):  
Renato C. Vieira ◽  
Marcelo B. Tenório ◽  
Mauro Roisenberg ◽  
Paulo S. S. Borges
Keyword(s):  
Rough Sets

TL-fuzzy set valued homomorphisms and generalized (I,T)-L-fuzzy rough sets on groups

Filomat ◽  
2017 ◽  
Vol 31 (13) ◽  
pp. 4153-4166
Author(s):  
Canan Ekiz ◽  
Muhammad Ali ◽  
Sultan Yamak
Keyword(s):  
Fuzzy Set ◽  
Rough Sets ◽  
Fuzzy Rough Sets
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