What's the common way to utilize distance functions for clustering?
Like does one set some thresholds for the distances and do grouping based on that?
What's the common way to utilize distance functions for clustering?
Like does one set some thresholds for the distances and do grouping based on that?
I worked on K-means clustering,
you dont need any thresholds for clustering the data, your algorithm with club your data into appropriate buckets, for each input data , your bucket entries will change, only one thing you need to do : define $k$, i.e number of buckets , usually, $k = n^\frac{1}{2}, n=$ number of data set.