A framework for benchmarking machine learning methods using linear models for univariate time series prediction
A framework for benchmarking machine learning methods using linear models for univariate time series prediction
Rebecca Salles,Laura Assis,3 作者,Eduardo Ogasawara
2017 · DOI: 10.1109/IJCNN.2017.7966139
IEEE International Joint Conference on Neural Network · 引用数 11
TLDR
A framework for systematic benchmarking some MLM against well-known Linear Methods (LM), namely Polynomial Regression and models in the ARIMA family, used as BM for univariate time series prediction is implemented within the R-Package named TSPred.