Right values for k and max run and dbscan epsilon and min point issue

Elu

Hi All,

Please i would like to know when one can tell the right values for k and max run when using kmeans algorithm. how do i also evaluate and interprete the results to know when k values is right? Is there a comprehensive video/material showing this? also how would i know the right value for epsilon and min point in DBSCAN. How do i evaluate and interprete results. Is there also a comprehensive video/material showing this? Thanks

rfuentealba

Hello, @Elu

Well, this is a tough question: although popular, establishing the value of k for a k-Means algorithm is a frequent topic of discussion and it depends on your experience. I can share two things with you today, though. One is that you may want to use x-Means, which is the same as a k-Means but it determines k based in a heuristic method rather than a manually added value. The other one is that you may want to use the elbow method to determine k, which is reasonable. A good tutorial on this can be found here.

Calculating epsilon and the min points on DBSCAN is the same principle, but using the k-NN distances in a matrix of points. Calculate the average distances of every point to the k-nearest neighbors, sort those in ascending order, plot the result and find where the knee cuts the Y value, that is your epsilon setting. The knee is the threshold where a change happens in the k distance curve. Now, I don't know how to determine k for this, as I've mostly used the same k as in a k-Means.

Hope this helps,

Rodrigo.