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This paper introduces a novel meta-learning algorithm for time series forecast model performance prediction.
“The algorithm selection problem”
J Rice · 1976
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Robert Cleveland, William Cleveland, Jean McRae and Irma Terpenning · 1990
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“Automatic forecasting software: A survey and evaluation”
Leonard Tashman and Michael Leach · 1991
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“Rule-based forecasting: development and validation of an expert systems approach to combining time series extrapolations”
Fred Collopy and J Armstrong · 1992
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“Combining and selecting forecasting models using rule based induction”
Bay Arinze, Seung-Lae Kim and Murugan Anandarajan · 1997
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“Model selection in univariate time series forecasting using discriminant analysis”
Chandra Shah · 1997
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“An intelligent model selection and forecasting system”
AR Venkatachalam and Jeffrey Sohl · 1999
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“An application of rule-based forecasting to a situation lacking domain knowledge”
Monica Adya, J Armstrong, Fred Collopy and Miles Kennedy · 2000
Earlier work this paper cites.
“Evidence for the selection of forecasting methods”
Nigel Meade · 2000
Earlier work this paper cites.
“Out-of-sample tests of forecasting accuracy: an analysis and review”
Leonard Tashman · 2000
Earlier work this paper cites.
“Automatic identification of time series features for rule-based forecasting”
Monica Adya, Fred Collopy, J Armstrong and Miles Kennedy · 2001
Earlier work this paper cites.
“Semiparametric regression”
D. Ruppert, M.P. Wand and R.J. Carroll · 2003
Earlier work this paper cites.
“Using machine learning techniques to combine forecasting methods”
Ricardo Prudêncio and Teresa Ludermir · 2004
Earlier work this paper cites.
“Meta-learning approaches to selecting time series models”
Ricardo Prudêncio and Teresa Ludermir · 2004
Earlier work this paper cites.
“Persistence in forecasting performance and conditional combination strategies”
Marco Aiolfi and Allan Timmermann · 2006
Earlier work this paper cites.
“Another look at measures of forecast accuracy”
Rob Hyndman and Anne Koehler · 2006
Cited alongside, same era.
“Characteristic-based clustering for time series data”
Xiaozhe Wang, Kate Smith and Rob Hyndman · 2006
Cited alongside, same era.
“Automatic time series forecasting: the forecast package for R”
Rob Hyndman and Yeasmin Khandakar · 2008
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“Visualizing data using t-SNE”
Laurens Maaten and Geoffrey Hinton · 2008
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“The WEKA data mining software: an update”
Mark Hall et al · 2009
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“Regression density estimation using smooth adaptive Gaussian mixtures”
Mattias Villani, Robert Kohn and Paolo Giordani · 2009
Cited alongside, same era.
“Visualising forecasting algorithm performance using time series instance spaces”
Yanfei Kang, Rob Hyndman and Kate Smith-Miles · 2017
Later among the works it cites.
“The M4 Competition: Results, findings, conclusion and way forward”
Spyros Makridakis, Evangelos Spiliotis and Vassilios Assimakopoulos · 2018
Later among the works it cites.
“Optimal selection of expert forecasts with integer programming”
Dmytro Matsypura, Ryan Thompson and Andrey Vasnev · 2018
Later among the works it cites.
“Exploring the sources of uncertainty: Why does bagging for time series forecasting work?”
Fotios Petropoulos, Rob Hyndman and Christoph Bergmeir · 2018
Later among the works it cites.
“Meta-learning how to forecast time series”, 2018
Thiyanga Talagala, Rob Hyndman and George Athanasopoulos · 2018
Later among the works it cites.
“Another look at forecast selection and combination: Evidence from forecast pooling”
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“Rule induction for forecasting method selection: meta-learning the characteristics of univariate time series”
Xiaozhe Wang, Kate Smith-Miles and Rob Hyndman · 2009
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Feng Li, Mattias Villani and Robert Kohn · 2010
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Feng Li and Mattias Villani · 2013
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Kenneth Lichtendahl, Yael Grushka-Cockayne and Robert Winkler · 2013
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“Model selection using dimensionality reduction of time series characteristics”
Agus Widodo and Indra Budi · 2013
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“‘Horses for Courses’ in demand forecasting”
F Petropoulos, S Makridakis, V Assimakopoulos and K Nikolopoulos · 2014
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Nikolaos Kourentzes, Devon Barrow and Fotios Petropoulos · 2019
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“microbenchmark: Accurate Timing Functions” R package version 1.4-7, 2019
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“Are forecasting competitions data representative of the reality?”
Evangelos Spiliotis, Andreas Kouloumos, Vassilios Assimakopoulos and Spyros Makridakis · 2019
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Anti Ingel et al · 2020
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“A simple combination of univariate models”
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“The uncertainty estimation of feature-based forecast combinations”
Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos and Feng Li · 2021
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