Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7548
Title: Subtree selection in kernels for graph classification
Authors: Tan, Mehmet
Polat, Faruk
Alhajj, Reda
Keywords: feature selection
classification
graph kernels
bioinformatics
cheminformatics
Issue Date: 2013
Publisher: Inderscience Enterprises Ltd
Abstract: 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.
URI: https://doi.org/10.1504/IJDMB.2013.056080
https://hdl.handle.net/20.500.11851/7548
ISSN: 1748-5673
1748-5681
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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