Global graph kernels using geometric embeddings
Authors: Fredrik Johansson, Vinay Jethava, Devdatt Dubhashi, Chiranjib Bhattacharyya
ICML 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate the Lov asz ϑ and SVM-ϑ kernels by performing graph classification of synthetic and benchmark datasets. We report the classification accuracy using 10fold cross-validation with a C-Support Vector Machine classifier, LIBSVM (Chang & Lin, 2011). |
| Researcher Affiliation | Academia | Fredrik D. Johansson FREJOHK@CHALMERS.SE Chalmers University of Technology, SE-412 96 Gothenburg, Sweden Vinay Jethava JETHAVA@CHALMERS.SE Chalmers University of Technology, SE-412 96 Gothenburg, Sweden Devdatt Dubhashi DUBHASHI@CHALMERS.SE Chalmers University of Technology, SE-412 96 Gothenburg, Sweden Chiranjib Bhattacharyya CHIRU@CSA.IISC.ERNET.IN Indian Institute of Science, Bangalore 560012 Karnataka, India |
| Pseudocode | No | The paper describes methods but does not include any formally structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide an explicit statement or link to its own open-source code for the described methodology. |
| Open Datasets | Yes | PTC (Predictive Toxicology Challenge) is a set of 417 chemical compound graphs labeled according to their carcinogenic effects on rats and mice (Helma et al., 2001). MUTAG (Debnath et al., 1991) is a dataset of 188 graphs representing mutagenetic compounds... ENZYME is a collection of 600 graphs representing tertiary protein structures collected by (Borgwardt et al., 2005)... NCI1 is a set of 4110 graphs representing a subset of chemical compounds screened for activity against non-small cell lung cancer cell lines (Wale et al., 2008). |
| Dataset Splits | Yes | We report the classification accuracy using 10fold cross-validation with a C-Support Vector Machine classifier, LIBSVM (Chang & Lin, 2011). |
| Hardware Specification | Yes | We report the CPU runtimes for computing each kernel on the benchmark experiments in Table 2, as measured in Matlab R2012a on a 3.4GHz Intel Core i7 with 4 cores and 32GB RAM. |
| Software Dependencies | Yes | as measured in Matlab R2012a on a 3.4GHz Intel Core i7 with 4 cores and 32GB RAM. ... LIBSVM (Chang & Lin, 2011). |
| Experiment Setup | Yes | The SVM parameter C was optimized for each kernel and fold and the best was used for the final accuracy. ... Both kernels were used with either the linear kernel k(x,y) = xy or the radial basis function kernel k(x,y) = e x y 2 2/(2σ2) with σ from the set [0.01,10]. |