A novel quad tree based data clustering technique

Data clustering is a branch of computation where division of data into groups of similar objects is made. Each group is formed with the data that are similar in some parametric values and dissimilar compared to data of other groups. Active research is being in progress with data clustering in several fields such as statistics, pattern recognition and machine learning. This paper proposes a data clustering technique based on quad tree. The current researchers established an algorithm, which is inspired by the construction and behavior of quad tree data structure. In its initiation, the algorithm has been tested thoroughly on synthetic data. The different set of results is found to be very encouraging for future investigation. The algorithm also shows nice execution time bound.