I've been using k-means clustering for bank customer segmentation up until now and I'm looking to explore other clustering algorithms in the banking domain. Is it a good idea to use affinity propagation algorithm for bank data? It will also be great if you can recommend me other algorithms frequently used for clustering in the banking domain.Thanks in advance.
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So the question asks for other clustering algorithms which can be used in customer segmentation.
In a similar way to using Affinity propagation to identify the "optimal" number of customer segments, to gain more control over the number of customer segments, you can also use agglomerative clustering (https://www.datanovia.com/en/lessons/agglomerative-hierarchical-clustering/), which is a bottom-up clustering method. Here, you can see how customer instances cluster (using a dendrogram) and determine an "optimal" number of customer segments from this.
