This is a simple implementation of K-means algorithm in MATLAB and Python. K-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster ...

In 2013-14, I was working on developing an integer linear programming formulation for an instance of the constrained clustering problem. The approach that I chose was Branch-and-Price (also referred ...

In practice, self-organizing map clustering is often used to validate k-means clustering. A relatively unexplored idea is to perform SOM clustering using an r-by-c map instead of a 1-by-k map. When ...

Then, you can use clustering results to custom tailor your marketing efforts. In this course, we will explore two popular clustering techniques: Agglomerative hierarchical clustering and K-means ...