  The paper addresses the graph classification problem and introduces a
modification of the lazy associative classification method to efficiently
handle intersections of graphs. Graph intersections are approximated with all
common subgraphs up to a fixed size similarly to what is done with graphlet
kernels. We explain the idea of the algorithm with a toy example and describe
our experiments with a predictive toxicology dataset.
