Search Results - subject:"Gradient Boosting Machines"

Short-term forecasting of the JSE All-Share Index using gradient boosting machines

Mukhaninga, Mueletshedzi; Ravele, Thakhani; Sigauke, Caston - In: Economies : open access journal 13 (2025) 8, pp. 1-25

This study applies Gradient Boosting Machines (GBMs) and principal component regression (PCR) to forecast the closing …

Persistent link: https://www.econbiz.de/10015447938

Short-term forecasting of the JSE All-Share Index using gradient boosting machines

Mukhaninga, Mueletshedzi; Ravele, Thakhani; Sigauke, Caston - In: Economies 13 (2025) 8, pp. 1-25

This study applies Gradient Boosting Machines (GBMs) and principal component regression (PCR) to forecast the closing …

Persistent link: https://www.econbiz.de/10015469913

Voluntary carbon reporting prediction : a machine learning approach

Frost, Geoffrey; Jones, Stewart; Yu, Muchen - In: Abacus : a journal of accounting, finance and business … 59 (2023) 4, pp. 1116-1166

Persistent link: https://www.econbiz.de/10014443595

A meta-learning based stacked regression approach for customer lifetime value prediction

Gadgil, Karan; Gill, Sukhpal Singh; Abdelmoniem, Ahmed M. - In: Journal of economy and technology 1 (2023), pp. 197-207

Companies across the globe are keen on targeting potential high-value customers in an attempt to expand revenue, and this could be achieved only by understanding the customers more. Customer lifetime value (CLV) is the total monetary value of transactions or purchases made by a customer with the...

Persistent link: https://www.econbiz.de/10014555514

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

Predictive Six Sigma for Turkish manufacturers: utilization of machine learning tools in DMAIC

Uluskan, Meryem - In: International Journal of Lean Six Sigma 14 (2023) 3, pp. 630-652

), random forests (RF), gradient boosting machines (GBM) and k-nearest neighbors (k-NN) in the analyze and improve phases of Six …

Persistent link: https://www.econbiz.de/10014782631

Interpretable machine learning for demand modeling with high-dimensional data using Gradient Boosting Machines and Shapley values

Antipov, Evgeny A.; Pokryshevskaya, Elena B. - In: Journal of revenue and pricing management 19 (2020) 5, pp. 355-364

Persistent link: https://www.econbiz.de/10012297970

GEFCom2012 hierarchical load forecasting : gradient boosting machines and Gaussian processes

Lloyd, James Robert - In: International journal of forecasting 30 (2014) 2, pp. 369-374

Persistent link: https://www.econbiz.de/10010510900

GEFCom2012 hierarchical load forecasting: Gradient boosting machines and Gaussian processes

Lloyd, James Robert - In: International Journal of Forecasting 30 (2014) 2, pp. 369-374

Global Energy Forecasting Competition 2012 hosted on Kaggle. The methods described (gradient boosting machines and Gaussian …

Persistent link: https://www.econbiz.de/10010753466