A Robust k-Means Clustering Algorithm Based on Observation Point Mechanism

Algorithm 1

Two-stage k-means clustering algorithm.

	Input:
	The number of clusters: k;
	The number of percentile: p;
	The original data set: ;
	Method:
	Normalize and generate ;
	for to d do
	Set where ;
	Generate by rearranging in ascending order and set be p-th percentile of ;
	Set and ;
	Equally divide the interval into intervals with length ;
	Let be the union of those intervals that contain local maximum number of elements in ;
	end for
	Select out a subset if and only if for all ;
	Refine and obtain the subsets :
	Perform the k-means algorithm on ;
	Assign each to the nearest center of the obtained cluster of ;
	Output:
	The result of clustering.