Abstract: Working on the group of personalcomputers and servers, a parallel C4.5 decision tree algorithm is proposed. This algorithm made the parallel date mining run on the data mining grid efficiently. A partition of vertical and horizontal method is introduced to parallel the procedure of recursive algorithm. The algorithm is scalable and solves the situation of lack of efficient parallel algorithm so far. The analysis and experiment for the parallel decision tree prove that the computing efficiency is affected by several parameters and the algorithm has high performance and high computing speedup. Guides to enhance the efficiency are proposed as well.

Key words: data mining, grid computing, decision tree, parallel performance