摘要
利用充分降维的思想对L2Boosting算法进行改进,提出基于局部相关性的L2Boosting(LCBoosting)算法。在每次迭代中,该算法根据响应变量与协变量的局部相关性充分提取信息,得到响应变量的线性组合来参与Boosting迭代,无须逐个分析所有变量。模拟结果表明,与L2Boosting算法相比,LCBoosting算法收敛速度快、预测精度高。
This paper improves L2Boosting algorithm by using the idea of sufficient dimension reduction and proposes a Local Correlation based L2Boosting（LCBoosting） algorithm.In each iteration,LCBoosting algorithm extracts information sufficiently according to the local correlation between response variable and covariant,gets a linear combination of response variable to join the Boosting iteration,and avoids analyzing all the variables one by one.Simulation results show that compared with L2Boosting algorithm,LCBoosting has better performance on the convergence rate and prediction precision.
出处
《计算机工程》
CAS
CSCD
北大核心
2010年第8期1-3,共3页
Computer Engineering
基金
国家自然科学基金资助项目(10771015)
中国人民大学研究生科研基金资助项目(22386104)
