Get the cluster-assignment probabilities for each instance, reassign these features to subject instances, and feed data back into polyssifier.
The centroids and assignments fields need to be assigned as part of the fit method (most likely using the predict_proba function), and we need to use the reassign_to_subjects function in the dFNC class to handle the multidimensional output to assign cluster probabilities as subject-level features.
We discussed taking the level of hierarchy with the best clustering scores as a hard assignment.
Get the cluster-assignment probabilities for each instance, reassign these features to subject instances, and feed data back into polyssifier.
The centroids and assignments fields need to be assigned as part of the fit method (most likely using the predict_proba function), and we need to use the reassign_to_subjects function in the dFNC class to handle the multidimensional output to assign cluster probabilities as subject-level features.
We discussed taking the level of hierarchy with the best clustering scores as a hard assignment.