A Fast Calculation of Metric Scores for Learning Bayesian Network  

作　　者：Qiang Lv Xiao-Yan Xia Pei-De Qian 

机构地区：[1]School of Computer Science and Technology, Soochow University, Suzhou 215006, PRC [2]Jiangsu Provincial Key Lab for Computer Information Processing Technology, Suzhou 215006, PRC

出　　处：《International Journal of Automation and computing》2012年第1期37-44,共8页国际自动化与计算杂志（英文版）

基　　金：supported by National Natural Science Foundation of China (No.60970055)

摘　　要：Frequent counting is a very so often required operation in machine learning algorithms. A typical machine learning task, learning the structure of Bayesian network （BN） based on metric scoring, is introduced as an example that heavily relies on frequent counting. A fast calculation method for frequent counting enhanced with two cache layers is then presented for learning BN. The main contribution of our approach is to eliminate comparison operations for frequent counting by introducing a multi-radix number system calculation. Both mathematical analysis and empirical comparison between our method and state-of-the-art solution are conducted. The results show that our method is dominantly superior to state-of-the-art solution in solving the problem of learning BN.Frequent counting is a very so often required operation in machine learning algorithms. A typical machine learning task, learning the structure of Bayesian network （BN） based on metric scoring, is introduced as an example that heavily relies on frequent counting. A fast calculation method for frequent counting enhanced with two cache layers is then presented for learning BN. The main contribution of our approach is to eliminate comparison operations for frequent counting by introducing a multi-radix number system calculation. Both mathematical analysis and empirical comparison between our method and state-of-the-art solution are conducted. The results show that our method is dominantly superior to state-of-the-art solution in solving the problem of learning BN.

关 键 词：Frequent counting radix-based calculation ADtree learning Bayesian network metric score 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TS102.211[自动化与计算机技术—控制科学与工程]