Publica
Hier finden Sie wissenschaftliche Publikationen aus den FraunhoferInstituten. Probabilistic frequent subtree kernels
 Ceci, M.: New frontiers in mining complex patterns : 4th international workshop, NFMCP 2015, held in conjunction with ECMLPKDD 2015, Porto, Portugal, September 7, 2015. Revised selected papers Cham: Springer, 2016 (Lecture Notes in Computer Science 9607) ISBN: 9783319393148 (print) ISBN: 9783319393155 pp.179193 
 International Workshop on New Frontiers in Mining Complex Patterns (NFMCP) <4, 2015, Porto> European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) <2015, Porto> 

 English 
 Conference Paper 
 Fraunhofer IAIS () 
Abstract
We propose a new probabilistic graph kernel. It is defined by the set of frequent subtrees generated from a small random sample of spanning trees of the transaction graphs. In contrast to the ordinary frequent subgraph kernel it can be computed efficiently for any arbitrary graphs. Due to its probabilistic nature, the embedding function corresponding to our graph kernel is not always correct. Our empirical results on artificial and realworld chemical datasets, however, demonstrate that the graph kernel we propose is much faster than other frequent pattern based graph kernels, with only marginal loss in predictive accuracy.