Part Priority Clustering Algorithm for Large-Scale Data Set

Abstract

The essay mainly studies the algorithm for large-scale data sets, namely, part priority algorithms. None of clustering algorithm can be true of all data sets. A kind of algorithm need to be matched with the realistic demand when faced with detailed data. As to part priority clustering algorithm, firstly, delete the data of first category from the data set after finding out the original data set, then repeat this step. The algorithm is put forward Based on efficiency and the simulation results show good results if less requirement for accuracy of data is made. Simulation results elaborated the steps of the algorithm in detail with the results showing the complexity of large-scale data and the feasibility of the algorithm.