Our Data Science Lab guru explains how to implement the k-means technique for data clustering, or cluster analysis, which is the process of grouping data items so that similar items belong to the same ...

In the proposed algorithm, they extend the K-Means clustering process to calculate a weight for each dimension in each cluster and use the weight values to identify the subsets of important ...

Because of this, k-means clustering can yield different results on different runs of the algorithm — which isn’t ideal in mission-critical domains like finance.