MOWM: Multiple Overlapping Window Method for RBF based missing value prediction on big data

作者：

Highlights：

• Enabling Radial Basis Function for surface fitting using Big Data and limited memory.

• Solution for missing value prediction on Big Data.

• Performance for missing value prediction is found better than Kernel Ridge Regression.

• Establishes bias variance tradeoff with the help of hyperparameters.

摘要

•Enabling Radial Basis Function for surface fitting using Big Data and limited memory.•Solution for missing value prediction on Big Data.•Performance for missing value prediction is found better than Kernel Ridge Regression.•Establishes bias variance tradeoff with the help of hyperparameters.

论文关键词：Missing value imputation,Interpolation,RBF,Kernel regression,MOWM,Big data,Machine learning,Curve fitting

论文评审过程：Received 13 May 2018, Revised 28 November 2018, Accepted 31 December 2018, Available online 2 January 2019, Version of Record 10 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.060