The IAM-Graph DB is structured as follows:

- Letter.zip - Contains the Letter graphs in three distortion levels.
- GREC.zip - Contains the GREC graphs.
- Fingerprint.zip - Contains the Fingerprint graphs.
- COIL-RAG.zip - Contains the COIL (RAG) graphs.
- COIL-DEL.zip - Contains the COIL (DEL) graphs.
- Web.zip - Contains the Webpage graphs.
- AIDS.zip - Contains the AIDS graphs.
- Mutagenicity.zip - Contains the Mutagenicity graphs.
- Protein.zip - Contains the Mutagenicity graphs.

The IAM-Graph DB is publicly accessible and freely available for non-commercial research purposes. If you are publishing scientific work based on the IAM-Graph DB, we request you to include a reference to our paper Riesen, K. and Bunke, H.: IAM Graph Database Repository for Graph Based Pattern Recognition and Machine Learning. In: da Vitora Lobo, N. et al. (Eds.), SSPR&SPR 2008, LNCS, vol. 5342, pp. 287-297, 2008. (SSPR '08 Paper).

- A train set composed of 250 compounds used to train SVM.
- A validation set composed of 250 compounds used to find parameters giving the best accuracy result.
- A test set composed of remaining 1500 compounds used to test the classification model.

Method | Classification accuracy (%) | |

(1) | Riesen and Bunke (2008) | 97.3 |

(2) | Suard et al. (2002) | 98.5 |

(3) | Vishwanathan et al. (2010) | 98.5 |

(4) | Neuhaus and Bunke (2007) | 99.7 |

(5) | Riesen et al. (2007) | 98.2 |

(6) | Graph Laplacian kernel | 99.3 |

(7) | Gauzere el al. (2012) | 99.1 |

- Gaüzère, B., et al. Two new graphs kernels in chemoinformatics. Pattern Recognition Lett. (2012), http://dx.doi.org/10.1016/j.patrec.2012.03.020.
- Neuhaus, M., Bunke, H., 2007. Bridging the Gap between Graph Edit Distance and Kernel Machines. World Scientific Pub Co Inc..
- Riesen, K., Neuhaus, M., Bunke, H., 2007. Graph embedding in vector spaces by means of prototype selection. In: Escolano, F., Vento, M. (Eds.), 6th IAPR-TC15 Internat. Workshop GbRPR 2007. IAPR TC15. Springer-Verlag, pp. 383–393.
- Riesen, K., Bunke, H., 2008. Iam graph database repository for graph based pattern recognition and machine learning. In: Proc. 2008 Joint IAPR Internat. Workshop on Structural, Syntactic, and Statistical Pattern Recognition. SSPR & SPR ’08. Springer-Verlag, Berlin, Heidelberg, pp. 287–297.
- Suard, F., Rakotomamonjy, A., Bensrhair, A., 2002. Kernel on bag of paths for measuring similarity of shapes. In: European Symposium on Artificial Neural Networks. pp. 355–360.
- Vishwanathan, S., Borgwardt, K.M., Kondor, I.R., Schraudolph, N.N., 2010. Graph kernels. J. Machine Learn. Res. 11, 1201–1242.