Benchmark dataset for graph classification

This repository contains datasets to quickly test graph classification algorithms, such as Graph Kernels and Graph Neural Networks. The purpose of this dataset is to make the features on the nodes and the adjacency matrix to be completely uninformative if considered alone. Therefore, an algorithm that relies only on the node features or on the graph structure will fail to achieve good classification results. A more detailed description of the dataset construction can be found on the Github page (https://github.com/FilippoMB/Benchmark_dataset_for_graph_classification), in the original publication and in the original publication: Bianchi, Filippo Maria, Claudio Gallicchio, and Alessio Micheli. \"Pyramidal Reservoir Graph Neural Network.\" Neurocomputing 470 (2022): 389-404, and in the README.txt file.