Graphlet-based lazy associative graph classification
Data Structures and Algorithms
2015-05-15 v2 Artificial Intelligence
Abstract
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.
Cite
@article{arxiv.1504.05457,
title = {Graphlet-based lazy associative graph classification},
author = {Yury Kashnitsky and Sergei O. Kuznetsov},
journal= {arXiv preprint arXiv:1504.05457},
year = {2015}
}
Comments
This paper has been withdrawn by the author due to the incomplete set of necessary definitions and experiments