Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)

Monotone Classification with Decision Trees

Authors
Marsala Christophe, Davide Petturiti
Corresponding Author
Marsala Christophe
Available Online August 2013.
DOI
https://doi.org/10.2991/eusflat.2013.120How to use a DOI?
Keywords
Fuzzy decision tree induction. Monotone classification. Measures of discrimination.
Abstract
In machine learning, monotone classification is concerned with a classification function to learn in order to guarantee a kind of monotonicity of the class with respect to attribute values. In this paper, we focus on rank discrimination measures to be used in decision tree induction, i.e., functions able to measure the discrimination power of an attribute with respect to the class taking into account the monotonicity of the class with respect to the attribute. Three new measures are studied in detail and an experimental analysis is also provided, comparing the proposed approach with other well-known monotone and non-monotone classifiers in terms of classification accuracy.
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Proceedings
8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
978-90786-77-78-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/eusflat.2013.120How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Marsala Christophe
AU  - Davide Petturiti
PY  - 2013/08
DA  - 2013/08
TI  - Monotone Classification with Decision Trees
BT  - 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/eusflat.2013.120
DO  - https://doi.org/10.2991/eusflat.2013.120
ID  - Christophe2013/08
ER  -