Subtree selection in kernels for graph classification


TAN M., POLAT F. , Alhajj R.

INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS, cilt.8, ss.294-310, 2013 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 8 Konu: 3
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1504/ijdmb.2013.056080
  • Dergi Adı: INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS
  • Sayfa Sayıları: ss.294-310

Özet

Classification of structured data is essential for a wide range of problems in bioinformatics and cheminformatics. One such problem is in silico prediction of small molecule properties such as toxicity, mutagenicity and activity. In this paper, we propose a new feature selection method for graph kernels that uses the subtrees of graphs as their feature sets. A masking procedure which boils down to feature selection is proposed for this purpose. Experiments conducted on several data sets as well as a comparison of our method with some frequent subgraph based approaches are presented.