Mastering Python for Data Science

The k-means clustering

The k-means clustering is an unsupervised learning technique that helps in partitioning data of n observations into K buckets of similar observations.

The clustering algorithm is called so because it operates by computing the mean of the features which refer to the dependent variables based on which we cluster things, such as segmenting of customers based on an average transaction amount and the average number of products purchased in a quarter of a year. This mean value then becomes the center of a cluster. The number K refers to the number of clusters, that is, the technique consisting of computing a K number of means, leading ...