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Author Girard, N. ♦ Bertet, K. ♦ Visani, M.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Special computer methods
Subject Keyword Lattices ♦ Context ♦ Iris recognition ♦ Navigation ♦ Databases ♦ Decision trees ♦ Glass ♦ Machine Learning ♦ Discretization ♦ Galois Lattices ♦ Classification
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.
ISBN 9781457720680
ISSN 10823409
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-11-07
Publisher Place USA
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9780769545967
Size (in Bytes) 127.89 kB
Page Count 2
Starting Page 902
Ending Page 903

Source: IEEE Xplore Digital Library