Journal of Universal Computer Science
In this paper the authors present an efficient data preprocessing procedure for the Support of Vector Clustering (SVC) to reduce the size of a training dataset. Solving the optimization problem and labeling the data points with cluster labels are time-consuming in the SVC training procedure. This makes using SVC to process large datasets inefficient. They proposed a data preprocessing procedure to solve the problem. The procedure contains a Shared Nearest Neighbor (SNN) algorithm, and utilizes the concept of unit vectors for eliminating insignificant data points from the dataset.