We'll look at hierarchical methods in this tutorial. As KMeans is based on distance from the cluster center to point in the cluster, it'll be able to cluster data that is organized globular/spherical shape and will fail to cluster data organized in a different manner. Create Isotropic Gaussian Blobs dataset & Skew Blobs Using TransformationĪ clustering algorithm like KMeans is good for clustering tasks as it is fast and easy to implement but it has limitations that it works well if data can be grouped into globular or spherical clusters and also one needs to provide a number of clusters.Create Isotropic Gaussian Blobs dataset.Create Dataset Of Circles (Large Circle Containing A Smaller Circle).Trying Agglomerative Clustering With Different Linkage.Create Moons Dataset (Two Interleaving Circles).Agglomerative Clustering - Average Linkage.Agglomerative Clustering - Complete Linkage.Agglomerative Clustering - Single Linkage.Hierarchical Clustering - Average Linkage.Hierarchical Clustering - Single Linkage.Hierarchical Clustering - Complete Linkage.I know that the linkage() function in scipy doesn't like 2d matrices (some bug I read about), but once the 2d matrix is read in, I convert it to a compressed matrix with squareform(distMatrix) as shown here: Use Distance Matrix in ()?.Īnyway, any ideas? I really have a hard time believing that scipy has the bug, but I'm running out of options.Scikit-Learn - Hierarchical Clustering ¶ Table of Contents ¶ I know the distance values are the same - I print them all ordered by size to a single string and calculate an md5 hash on that string, and the hash is always the same. Here's the trick: when I change the ordering scheme - maybe sort by size, or even a random number generator - python calculates different numbers of clusters for the same cutoff. save out the distance so that it can be written to a 2d matrix My code looks more or less like this: var set = set.OrderBy(x => x.GetHashCode()) Here's the problem: I need to impose some kind of ordering on them so that they have an ordering along each axis. I have a C# program that does some analysis, prints out a full 2D matrix of distance values, and then launches a scipy python process (anaconda, fwiw) to do hierarchical clustering.

Scipy linkage