In fit_predict I see the labels are returned. Each individual label is assigned to the nearest microcluster and hence every point has a label. Yet we are using dbscan in this methodology which allows for non-assignment of points. Is there a way to adapt this code to have some points not labeled (e.g. -1) for points which are outliers. In practice, I see that there are some points which are too far away from the centers yet could not reasonably belong to any other microcluster and this should be unassigned.
In
fit_predictI see the labels are returned. Each individual label is assigned to the nearest microcluster and hence every point has a label. Yet we are using dbscan in this methodology which allows for non-assignment of points. Is there a way to adapt this code to have some points not labeled (e.g. -1) for points which are outliers. In practice, I see that there are some points which are too far away from the centers yet could not reasonably belong to any other microcluster and this should be unassigned.