On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19.
Sandra Benítez-PeñaEmilio CarrizosaVanesa GuerreroMaría-Dolores Jiménez-GameroBelén Martín-BarragánCristina Molero-RíoPepa Ramírez-CoboDolores Romero MoralesM. Remedios Sillero-DenamielPublished in: Eur. J. Oper. Res. (2021)
Keyphrases
- short term
- ensemble methods
- long term
- prediction accuracy
- ensemble learning
- random forests
- machine learning methods
- base learners
- decision trees
- base classifiers
- short term and long term
- generalization ability
- drifting concepts
- short term prediction
- benchmark datasets
- load forecasting
- stock market
- bootstrap sampling
- high dimensional
- random forest
- wind speed
- forecasting model
- long term memory
- short and long term
- medium term
- classifier ensemble
- training data
- data sets
- logistic regression
- concept drift
- arima model
- pattern recognition