Why is the tox21 dataset loaded with predefined 12 classes when it should be binary classification, thus two classes?
Code sampled modified:
import rdkit from torch_geometric.datasets import MoleculeNet # Load the Tox21 dataset data = MoleculeNet(root=".", name="Tox21") print("Dataset type: ", type(data)) print("Dataset features: ", data.num_features) print("Dataset target: ", data.num_classes) print("Dataset length: ", data.len) > Dataset type: <class 'torch_geometric.datasets.molecule_net.MoleculeNet'> > Dataset features: 9 > Dataset target: 12
I'm borrowing code from this post.
There are 12 assays, so one could train and test by assay, in which case we would end up with a Toxic|non-toxic (two classes) for each assay.
How do I setup the data class to work by group (e.g., by assay)?