Fast shortest-path kernel computations using aproximate methods
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Typ
Examensarbete för masterexamen
Master Thesis
Master Thesis
Program
Computer science – algorithms, languages and logic (MPALG), MSc
Publicerad
2015
Författare
Kilhamn, Jonatan
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
The shortest-path kernel is frequently seen in the context of graph classification, which shows up in various subjects, for example bioinformatics. However, it is not efficient enough to be applicable in practice if the graphs are too large. The purpose of this thesis is to explore the possibilities of computing the shortest-path kernel approximately, taking shorter time at the cost of a limited error. This thesis proves a theoretical error bound for a class of kernel function approximations, applicable to the shortest-path kernel but further generaliseable as well. We also present two specific approximations of the shortest-path kernel. Firstly, we define an approximate kernel based on the idea of sampling node pairs in a graph to approximate its shortest-path length distribution. Secondly, we define a kernel computing approximate shortest-path lengths in a graph using its graph Voronoi dual. We provide algorithms to compute both of these, and prove that their runtime complexities are better than the shortest-path kernel they approximate. Finally, we evaluate these kernel approximations empirically, comparing them to the full shortest-path kernel as well as other reference kernels.
Beskrivning
Ämne/nyckelord
Data- och informationsvetenskap , Computer and Information Science