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04/04/2023
Handling Concept Drift in Global Time Series Forecasting
Machine learning (ML) based time series forecasting models often require...
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11/16/2022
SETAR-Tree: A Novel and Accurate Tree Algorithm for Global Time Series Forecasting
Threshold Autoregressive (TAR) models have been widely used by statistic...
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05/14/2021
Monash Time Series Forecasting Archive
Many businesses and industries nowadays rely on large quantities of time...
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12/30/2020
Ensembles of Localised Models for Time Series Forecasting
With large quantities of data typically available nowadays, forecasting ...
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10/16/2020
A Strong Baseline for Weekly Time Series Forecasting
Many businesses and industries require accurate forecasts for weekly tim...
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06/27/2020
Seasonal Averaged One-Dependence Estimators: A Novel Algorithm to Address Seasonal Concept Drift in High-Dimensional Stream Classification
Stream classification methods classify a continuous stream of data as ne...
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06/27/2020
