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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.
The text was updated successfully, but these errors were encountered:
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.The text was updated successfully, but these errors were encountered: