Unsupervised Machine Learning - Hierarchical Clustering of points (Dataset)

Hello Everyone,
I wanted to implement Unsupervised machine learning for creating the optimized cluster of points.

I got know multiple algorithm but i feels , Hierarchical clustering (H-clustering) algorithm is best as per my dataset thats why i wanna use Hierarchical clustering algorithm on points.

On google, you will find multiple python script for this algorithm.
Currently i am facing an issue on import function need to be used in dynamo python script and i dont know which function need to be import for running this script, etc. and my copy past script wont work directly on my dynamo environment. we need to edit those script as per dynamo environment as per per out inputs.

As i have shown in the image below, inputs will be points and number of cluster need to be formed and expected outcome will be cluster of points showing in the image. (in real case scenario, group of points wont be in a rectangular format, points might be randomly distributed on a surface with curve boundary)


Few link which i refer for creating Hierarchical clustering node are,

2 Likes

I think it depends on the data we have, I’m also working on some architectural projects, thanks for the interesting information.

Hello @chuongpqvn , i agree, it depend upon data which we have and
i know, my data set will be point align with the grid (horizontal and vertical, spacing between grid might change) and number of point might be same or different compare in a row or column.
if you get any node to script, please let me know

I would to add one more point in my above Topic,

Another method of clustering the point k-mean clustering and got that node in “Sparrow package”
but that type of clustering is not my ideal solution, that why i am looking for Hierarchical clustering of dataset.