Framework : ObjAsm C.2 - masters : Main Developer , Fork - working version 6 march 2024
Some weeks ago I found the article: Comparing K-Means and Others Algorithms for Data Clustering by Nicolás Descartes. With C# source code.
Look very interesting to translate that to Assembly. Still is a work in progress but look well.
There is some kind of abuse of Collections, because is very easy to write that in C#. I removed most obvious exagerations (perhaps author try to make more clear the algorithm, not sure).
-
K-Means strategy need initial randomness, then probably you have to run several times before to find the better solution.
-
Hierarchical strategy need to define termination, and in these cases are number of clusters.
-
Density-based spatial clustering of applications with noise really benefit from Collections, and also need a couple of Sorted Vectors.
Anyway is a good challenge, and still I have to collect some leaks
Original discussion can be found in Masm32 Forum
Any sugestion or improvement is welcome!