The K-Means Algorithm Process. The dataset is partitioned into K clusters and the data points are randomly assigned to the clusters resulting in clusters that have roughly the same number of data points. For each data point: Calculate the distance from the data point to each cluster.he version of the K-Means algorithm used in GeneLinker differs from the conventional K-Means algorithm in that GeneLinker does not compute the centroid of the clusters to measure the distance from a data point to a cluster.