Search Results - subject:"GRADIENT BOOSTING"

Gradient boosting for convex cone predict and optimize problems

Butler, Andrew; Kwon, Roy H. - In: Operations research letters 51 (2023) 1, pp. 79-83

Persistent link: https://www.econbiz.de/10014283299

Exploring drivers of staff engagement in healthcare organizations using tree-based machine learning algorithms

Al-Nammari, Ragheb; Simsekler, Mecit Can Emre; Gabor, … - In: IEEE transactions on engineering management : EM 70 (2023) 8, pp. 2988-2997

Persistent link: https://www.econbiz.de/10014364805

A high-dimensional approach to predicting audit opinions

Saeedi, Ali - In: Applied economics 55 (2023) 33, pp. 3807-3832

Persistent link: https://www.econbiz.de/10014299226

Baseball informatics : from MiLB to MLB debut

Lee, Chung-Hao; Lee, Woei-jyh - In: Analytics Enabled Decision Making, (pp. 89-122). 2023

Persistent link: https://www.econbiz.de/10014302860

Interpreting the prediction results of the tree-based gradient boosting models for financial distress prediction with an explainable machine learning approach

Liu, Jiaming; Li, Chengzhang; Ouyang, Peng; Liu, Jiajia; … - In: Journal of forecasting 42 (2023) 5, pp. 1112-1137

Persistent link: https://www.econbiz.de/10014338816

An explainable artificial intelligence approach to understanding drivers of economic energy consumption and sustainability

Srivastava, Praveen Ranjan; Mangla, Sachin Kumar; … - In: Energy economics 125 (2023), pp. 1-21

Persistent link: https://www.econbiz.de/10014484405

The role of feature importance in predicting corporate financial distress in pre and post COVID periods : evidence from China

Ding, Shusheng; Cui, Tianxiang; Bellotti, Anthony Graham; … - In: International review of financial analysis 90 (2023), pp. 1-9

Persistent link: https://www.econbiz.de/10014469979

Integrating operational and human factors to predict daily productivity of warehouse employees using extreme gradient boosting

Falkenberg, Sven F.; Spinler, Stefan - In: International journal of production research 61 (2023) 24, pp. 8654-8673

: warehouse, operator, shift and product. We demonstrate that Extreme Gradient Boosting, using these variables may reduce the root … Moving Averages; EGB: Extreme Gradient Boosting; GB: Gradient Boosting; LSP: Logistics Service Provider; MAE: Mean Absolute …

Persistent link: https://www.econbiz.de/10014454501

Machine learning and the cross-section of emerging market stock returns

Hanauer, Matthias Xaver; Kalsbach, Tobias - In: Emerging markets review 55 (2023), pp. 1-38

Persistent link: https://www.econbiz.de/10014481087

Predicting stock splits using ensemble machine learning and SMOTE oversampling

Li, Ang; Liu, Mark H.; Sheather, Simon J. - In: Pacific-Basin finance journal 78 (2023), pp. 1-24

Persistent link: https://www.econbiz.de/10014463767