Classifying nodes with vanilla neural networks
Compared to Zachary’s Karate Club, these two datasets include a new type of information: node features. They provide additional information about the nodes in a graph, such as a user’s age, gender, or interests in a social network. In a vanilla neural network (also called multilayer perceptron), these embeddings are directly used in the model to perform downstream tasks such as node classification.
In this section, we will consider node features as a regular tabular dataset. We will train a simple neural network on this dataset to classify our nodes. Note that this architecture does not take into account the topology of the network. We will try to fix this issue in the next section and compare our results.
The tabular dataset of node features can be easily accessed through the data object we created. First, I would like to convert this object into a regular pandas DataFrame by merging data.x (containing the node features...
