DocumentCode
2752214
Title
Gradual fuzzy decision trees to help medical diagnosis
Author
Marsala, Christophe
Author_Institution
LIP6, Univ. Pierre et Marie Curie, Paris, France
fYear
2012
fDate
10-15 June 2012
Firstpage
1
Lastpage
6
Abstract
In this paper, we consider the problem of the construction of fuzzy decision trees when there exists a graduality between the values of attributes and values of the class. We propose a new measure, extended from the measure of classification ambiguity, that takes into account both discrimination power and graduality with regards to the class. To highlight the importance of that kinds of measures, Medical applications is presented in which often the values of the class are symbolic and ordered and in which the discovery of gradual links between descriptive attributes and the class are seek for.
Keywords
decision trees; fuzzy set theory; learning (artificial intelligence); medical computing; patient diagnosis; pattern classification; classification ambiguity; discrimination power; gradual fuzzy decision trees; medical applications; medical diagnosis; Biomedical equipment; Decision trees; Entropy; Indexes; Medical services; Power measurement; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location
Brisbane, QLD
ISSN
1098-7584
Print_ISBN
978-1-4673-1507-4
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZ-IEEE.2012.6251147
Filename
6251147
Link To Document