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Confused by DBSCAN min points #6
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@awenger Thanks for your comment! As far as I understand the algorithm, this is correct behaviour. Yes, I agree with you it may be confusing and all parameters needs brief explanation.
What do you think? |
@lukaszkrawczyk I'm also not 100% sure. But if I look at wikipedia it describes the parameters as: The pseudocode for regionQuery also includes the point that was used to query the neighborhood [1]:
I guess this is different in this DBSCAN implementation: https://github.com/LukaszKrawczyk/clustering/blob/master/lib/DBSCAN.js#L184 What do you think? |
Yes... there was a similar discussion on including core point in OPTICS algorithm some time ago: I checked how it's implemented in other libraries (such as e.g. SciKit), and I'm more and more confident we should change the algorithm to include core points, both in DBSCAN and OPTICS. I will modify code and update package on NPM. |
Thanks a lot for the update |
I modified the sample and all the points are marked as noise if you increase the min points value to 3:
I'm not sure whether this is the intended behavior for DBSCAN. I think this should be fixed or documented. What do you think?
I guess this could be fixed arround here: https://github.com/LukaszKrawczyk/clustering/blob/master/lib/DBSCAN.js#L68
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