Simply speaking it is an algorithm to classify or to group your objects based on attributes/features into K
number of group. K is positive integer number. The grouping is done by minimizing the sum of squares of
distances between data and the corresponding cluster centroid. Thus, the purpose of K-mean clustering is to
classify the data.