DocumentCode :
2652074
Title :
Local Discretization of Numerical Data for Galois Lattices
Author :
Girard, Nathalie ; Bertet, Karell ; Visani, Muriel
Author_Institution :
Lab. L3i, Univ. of La Rochelle, La Rochelle, France
fYear :
2011
fDate :
7-9 Nov. 2011
Firstpage :
902
Lastpage :
903
Abstract :
Galois lattices´ (GLs) definition is defined for a binary table (called context). Therefore, in the presence of continuous data, a discretization step is needed. Discretization is classically performed before the lattice construction in a global way. However, local discretization is reported to give better classification rates than global discretization when used jointly with other symbolic classification methods such as decision trees (DTs). We present a new algorithm performing local discretization for GLs using the lattice properties. Our local discretization algorithm is applied iteratively to particular nodes (called concepts) of the GL. Experiments are performed to assess the efficiency and the effectiveness of the proposed algorithm compared to global discretization.
Keywords :
Galois fields; decision trees; iterative methods; numerical analysis; pattern classification; Galois lattice property; binary table; classification rate; continuous data; decision tree; global discretization; lattice construction; local discretization algorithm; numerical data; symbolic classification method; Context; Databases; Decision trees; Glass; Iris recognition; Lattices; Navigation; Classification; Discretization; Galois Lattices; Machine Learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
Conference_Location :
Boca Raton, FL
ISSN :
1082-3409
Print_ISBN :
978-1-4577-2068-0
Electronic_ISBN :
1082-3409
Type :
conf
DOI :
10.1109/ICTAI.2011.148
Filename :
6103439
Link To Document :
بازگشت