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Estimating city-level poverty rate based on e-commerce data with machine learning

Wijaya, Dedy Rahman; Paramita, Ni Luh Putu Satyaning Pradnya - In: Electronic commerce research 22 (2022) 1, pp. 195-221

Persistent link: https://www.econbiz.de/10013169448

Powering retailers' digitization through analytics and automation

Simchi-Levi, David; Wu, Michelle Xiao - In: International journal of production research 56 (2018) 1/2, pp. 809-816

Persistent link: https://www.econbiz.de/10011877132

Using machine learning to assess the predictive potential of standardized nursing data for home healthcare case-mix classification

Korte, Maud H. de; Verhoeven, Gertjan S.; Elissen, … - In: The European journal of health economics : HEPAC ; … 21 (2020) 8, pp. 1121-1129

Persistent link: https://www.econbiz.de/10012490426

Evaluation of machine learning applications using real-world EHR data for predicting diabetes-related long-term complications

Mosa, Abu Saleh Mohammad; Thongmotai, Chalermpon; … - In: Journal of business analytics 5 (2022) 2, pp. 141-151

Persistent link: https://www.econbiz.de/10013453962

Machine learning methods in finance : recent applications and prospects

Hoang, Daniel; Wiegratz, Kevin - In: European financial management : the journal of the … 29 (2023) 5, pp. 1657-1701

Persistent link: https://www.econbiz.de/10014430234

Comparative analysis of methods for prediction continuous numerical features on big datasets

Kinshakov, Eduard; Parfenenko, Yuliia; Shendryk, Vira - In: Technology audit and production reserves 6 (2021) 2/62, pp. 15-17

Persistent link: https://www.econbiz.de/10013167729

Does high-frequency social media data improve forecasts of low-frequency consumer confidence measures?

Lehrer, Steven F.; Xie, Tian; Zeng, Tao - In: Journal of financial econometrics 19 (2021) 5, pp. 910-933

Persistent link: https://www.econbiz.de/10012799054

Option return predictability with machine learning and big data

Bali, Turan G.; Beckmeyer, Heiner; Mörke, Mathis; … - 2021 - This version: August 20, 2021

Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. Besides statistical significance, the...

Persistent link: https://www.econbiz.de/10012620725

Predicting poverty and malnutrition for targeting, mapping, monitoring, and early warning

McBride, Linden; Barrett, Christopher B.; Browne, … - In: Applied economic perspectives and policy 44 (2022) 2, pp. 879-892

Persistent link: https://www.econbiz.de/10013274051

Scaled PCA : a new approach to dimension reduction

Huang, Dashan; Jiang, Fuwei; Li, Kunpeng; Tong, Guoshi; … - In: Management science : journal of the Institute for … 68 (2022) 3, pp. 1678-1695

Persistent link: https://www.econbiz.de/10013260016

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