Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model.
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%0 Journal Article
%1 journals/isci/ParmezanSB19
%A Parmezan, Antonio Rafael Sabino
%A de Souza, Vinícius M. A.
%A Batista, Gustavo E. A. P. A.
%D 2019
%J Inf. Sci.
%K dblp
%P 302-337
%T Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model.
%U http://dblp.uni-trier.de/db/journals/isci/isci484.html#ParmezanSB19
%V 484
@article{journals/isci/ParmezanSB19,
added-at = {2019-04-12T00:00:00.000+0200},
author = {Parmezan, Antonio Rafael Sabino and de Souza, Vinícius M. A. and Batista, Gustavo E. A. P. A.},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/24c21864704c805931ad6d54e0cf2154b/dblp},
ee = {https://doi.org/10.1016/j.ins.2019.01.076},
interhash = {756a8ec4dd0cfc481c77241302de2f2c},
intrahash = {4c21864704c805931ad6d54e0cf2154b},
journal = {Inf. Sci.},
keywords = {dblp},
pages = {302-337},
timestamp = {2019-09-27T06:40:03.000+0200},
title = {Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model.},
url = {http://dblp.uni-trier.de/db/journals/isci/isci484.html#ParmezanSB19},
volume = 484,
year = 2019
}
