Local discretization of numerical data for Galois Lattices

Nathalie Girard (1) , Karell Bertet (1) , Muriel Visani (1)

1 L3I - Laboratoire Informatique, Image et Interaction - EA 2118

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.

Mots clés: Discretization; Galois Lattices; Classification; Machine Learning

Domaines: Apprentissage [cs.LG]; Intelligence artificielle [cs.AI]

Nathalie Girard, Karell Bertet, Muriel Visani. Local discretization of numerical data for Galois Lattices. ICTAI 2011, Nov 2011, Boca Raton, Florida, United States. pp.902-903, ⟨10.1109/ICTAI.2011.148⟩. ⟨hal-00640987⟩