The purpose of 'forecastML' is to simplify the process of multistepahead forecasting with standard machine learning algorithms. 'forecastML' supports lagged, dynamic, static, and grouping features for modeling single and grouped numeric or factor/sequence time series. In addition, simple wrapper functions are used to support modelbuilding with most R packages. This approach to forecasting is inspired by Bergmeir, Hyndman, and Koo's (2018) paper "A note on the validity of crossvalidation for evaluating autoregressive time series prediction" <doi:10.1016/j.csda.2017.11.003>.
Package details 


Author  Nickalus Redell 
Maintainer  Nickalus Redell <nickalusredell@gmail.com> 
License  MIT + file LICENSE 
Version  0.9.0 
URL  https://github.com/nredell/forecastML/ 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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