International Journal of Innovative Science Engineering and Technology (IJISET)
Cluster labeling is a framework or processing large data sets and also used to do distribute computing on clusters of computer. These Cluster Labeling libraries have been written in many programming languages. Here, the authors propose two novel algorithms for an efficient cluster labeling methods, support vector (parallel support vector) and mining methods (parallel mining methods), which facilitate simultaneous participation of multiple computing nodes to construct a boosted classifier. They analyze the problems in the existing system and try to solve it by using these two algorithms in their proposed system. In this paper, they outlined the procedure for applying the two cluster labeling methods and the impact of the methods.