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Forecasting with gradient boosted trees : augmentation, tuning, and cross-validation strategies : winning solution to the M5 uncertainty competition
Lainder, A. David; Wolfinger, Russell D. - In: International journal of forecasting 38 (2022) 4, pp. 1426-1433
Persistent link: https://www.econbiz.de/10014381101
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Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series
Nasios, Ioannis; Vogklis, Konstantinos - In: International journal of forecasting 38 (2022) 4, pp. 1448-1459
Persistent link: https://www.econbiz.de/10014381109
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Box office forecasting using machine learning algorithms based on SNS data
Kim, Taegu; Hong, Jungsik; Kang, Pilsung - In: International journal of forecasting 31 (2015) 2, pp. 364-390
Persistent link: https://www.econbiz.de/10011474110
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Predictive analysis and modelling football results using machine learning approach for English Premier League
Baboota, Rahul; Kaur, Harleen - In: International journal of forecasting 35 (2019) 2, pp. 741-755
Persistent link: https://www.econbiz.de/10012300725
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Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers : a study of Tema General Hospital of Ghana
Twumasi, Clement; Twumasi, Juliet - In: International journal of forecasting 38 (2022) 3, pp. 1258-1277
Persistent link: https://www.econbiz.de/10013349668
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Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks
Barkan, Oren; Benchimol, Jonathan; Caspi, Itamar; … - In: International journal of forecasting 39 (2023) 3, pp. 1145-1162
Persistent link: https://www.econbiz.de/10014465250
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A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks
Elalem, Yara Kayyali; Maier, Sebastian; Seifert, Ralf W. - In: International journal of forecasting 39 (2023) 4, pp. 1874-1894
Persistent link: https://www.econbiz.de/10014465364
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Predicting bank insolvencies using machine learning techniques
Petropoulos, Anastasios; Siakoulis, Vasilis; … - In: International journal of forecasting 36 (2020) 3, pp. 1092-1113
Persistent link: https://www.econbiz.de/10012497724
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A hybrid machine learning model for forecasting a billing period’s peak electric load days
Saxena, Harshit; Aponte, Omar; McConky, Katie T. - In: International journal of forecasting 35 (2019) 4, pp. 1288-1303
Persistent link: https://www.econbiz.de/10012305279
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Demand forecasting for fashion products : a systematic review
Swaminathan, Kritika; Venkitasubramony, Rakesh - In: International journal of forecasting 40 (2024) 1, pp. 247-267
Persistent link: https://www.econbiz.de/10014450269