K-Means vs. Affinity Propagation Clustering

Author(s): Michelangiolo Mazzeschi

Originally published on Towards AI.

Finding Clusters

Clustering is one of the simplest algorithms to implement with any Machine Learning tools. There are two different sets of algorithms dedicated to Clustering, depending on if we use Numerical Data (K-Means or Affinity Propagation), or Categorical Data (K-Mode).

Example of Clustering

Because with Categorical Clustering your data is not encoded in any mathematical space (you could solve that with labeling, but you would forcibly associate a numerical value to each one of your categories) it is very hard to deal with. You need to choose a specific algorithm and perform analysis using different metrics and evaluation methods. Therefore, in this article,… Read the full blog for free on Medium.

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Published via Towards AI