A Feature Coinciding Walk Kernel classifies nodes in a graph.
This project is a python port of Coinciding Walk Kernels (CWK) [1] and introduces an extension of the model called Feature-CWK (FCWK). If you want to jump right into some code see the benchmark.
CW-Kernels deal with the problem of node classification (aka link-based classification) in which a set of features and labels for items are given just as in regular classification. In addition, a node classification algorithm accepts a graph of of items and item-item links. It has been shown that the additional information that is inherent in the network structure improves performance for certain algorithms and datasets.