Machine learning: clustering

K-means' goal is to reveal patterns within the data. Let's imagine that you have a database with millions of rows representing your customers' orders. You might want to use the K-means algorithm to gather your customers into different groups based on key characteristics. K-means is easy to implement; you just need to specify how many clusters you want. Here you should look at two measures.