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 ...

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.

In this paper, the authors contain a partitional based algorithm for clustering high-dimensional objects in subspaces for iris gene dataset. In high dimensional data, clusters of objects often ...

Unlike many clustering algorithms, including k-means, the EMIAC algorithm can be easily modified to deal with numeric data or mixed numeric and categorical data. The idea is to preprocess numeric data ...