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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 Auteurs,Eduardo Ogasawara
2017 · DOI: 10.1109/IJCNN.2017.7966139
IEEE International Joint Conference on Neural Network · 11 citations
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.