labeled DBSCAN clustering with map on labels, how to easily find working epsilon/min points?
pvds90
New Altair Community Member
Hi guys,
I have 1 labeled attribute and i want to use DBSCAN. Is there a way how i can easily find what epsilon and min points are a fit? Now I'm trying randomly, but this is very time consuming.
I have 1 labeled attribute and i want to use DBSCAN. Is there a way how i can easily find what epsilon and min points are a fit? Now I'm trying randomly, but this is very time consuming.
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Best Answer
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The easiest way is to place the clustering operator together with a number of "daisy-chained" cluster performance operators within an Optimize Parameters (Grid). The optimizer will allow you to vary DBSCAN parameters, such as epsilon and the minimum points, while performance is collected and logged for each combination of these parameters. At the end (and while it is executing) you can watch and plot the logged values. Note that DBSCAN is slow on very large data sets, so I suggest to take a smaller data sample and initially vary the parameters in large steps. Once you find the best "cube" of your parameters, tune the parameters with the finer comb.
5
Answers
-
The easiest way is to place the clustering operator together with a number of "daisy-chained" cluster performance operators within an Optimize Parameters (Grid). The optimizer will allow you to vary DBSCAN parameters, such as epsilon and the minimum points, while performance is collected and logged for each combination of these parameters. At the end (and while it is executing) you can watch and plot the logged values. Note that DBSCAN is slow on very large data sets, so I suggest to take a smaller data sample and initially vary the parameters in large steps. Once you find the best "cube" of your parameters, tune the parameters with the finer comb.
5