Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition
Eugen Barbu, Romain Raveaux, Hervé Locteau, S. Adam, Pierre Héroux, Éric Trupin · 2006
We present in this paper a graph classification approach using genetic algorithm and a fast dissimilarity measure between graphs called graph probing. The approach consists in the learning of a set of synthetic graph prototypes which are used for a 1NN classification step. Some experiments are performed on real data sets, representing 10 symbols. These tests demonstrate the interest to produce prototypes instead of finding representatives which simply belong to the data set