RMARS: Robustification of multivariate adaptive regression spline under polyhedral uncertainty
作者:
Highlights:
• By the robust optimization technique we refine the regression and classification method MARS.
• Related to this, we involve the existence of uncertainty in this data mining tool.
• We present Robust MARS (RMARS) in theory and method.
• We show that models from RMARS have much less variability in parameter estimates.
• We also show that models from RMARS have less variability in accuracy measures.
摘要
•By the robust optimization technique we refine the regression and classification method MARS.•Related to this, we involve the existence of uncertainty in this data mining tool.•We present Robust MARS (RMARS) in theory and method.•We show that models from RMARS have much less variability in parameter estimates.•We also show that models from RMARS have less variability in accuracy measures.
论文关键词:MARS,Robust optimization,Polyhedral uncertainty,RMARS,Finance
论文评审过程:Received 9 February 2013, Revised 27 July 2013, Available online 10 October 2013.
论文官网地址:https://doi.org/10.1016/j.cam.2013.09.055