Search Results - subject:"Random Forest"

Verbesserung der Data-Matching-Qualität mit optimierter String-Distanz-Metrik-Auswahl und Random Forest

Nölting, Christopher; Hajiyev, Murad - In: WISTA - Wirtschaft und Statistik 77 (2025) 5, pp. 69-81

Random-Forest-Modell kombiniert. Durch Datenbereinigung, Balanced Sampling und Negativmatches entsteht ein robuster Workflow … random forest model. Data cleaning, balanced sampling, and negative matches create a robust workflow for record linkage. The …

Persistent link: https://www.econbiz.de/10015508441

Verbesserung der Data-Matching-Qualität mit optimierter String-Distanz-Metrik-Auswahl und Random Forest

Nölting, Christopher; Hajiyev, Murad - In: Wirtschaft und Statistik : WISTA (2025) 5, pp. 69-81

Persistent link: https://www.econbiz.de/10015481411

Predicting buildings' EPC in Italy : a machine learning based-approach

Braggiotti, Francesco; Chiarini, Nicola; Dondi, Giulio; … - 2024

Persistent link: https://www.econbiz.de/10014634359

Predicting bank distress in Europe: Using machine learning and a novel definition of distress

Malikkidou, Despo; Strohbach, Wolfgang - 2025

learning techniques against the traditional logistic model. We find that the random forest model shows superior performance …

Persistent link: https://www.econbiz.de/10015199522

Skills, job application strategies, and the gender wage gap: Evidence from online freelancing

Teutloff, Ole; Stenzhorn, Eliza; Kässi, Otto - 2025

This paper examines how worker skills and job application behavior contribute to the gender wage gap on a major online freelancing platform. We observe significant occupational sorting by gender, with women over-represented in lower-paying project categories and tending to earn less than men...

Persistent link: https://www.econbiz.de/10015338542

A Machine‐Learning Approach to Understanding Performance of Canadian Nonprofit Sport Organizations

Yang, Yanxiang; Byers, Terri; Koenigstorfer, Joerg - In: Nonprofit Management and Leadership 35 (2025) 3, pp. 663-675

. Explanatory linear regressions and four machine‐learning models (i.e., ridge regression, bagged regression, random forest, and … linear models. The random forest outperforms the other models in terms of root mean squared error and, partly, mean absolute …

Persistent link: https://www.econbiz.de/10015411062

Comparing the Prediction Performance of Random Forest, Lasso, and Logit in the Context of IPO Withdrawal

Reiff, Annika - In: Intelligent Systems in Accounting, Finance and Management 32 (2025) 3

This paper examines the prediction of IPO withdrawal using machine learning methods (lasso and random forest) and … conventional regression (logit). The dataset comprises 2444 US first‐time IPOs from 1997 to 2014. Results show that random forest …

Persistent link: https://www.econbiz.de/10015441429

A machine-learning approach to understanding performance of Canadian nonprofit sport organizations

Yang, Yanxiang; Byers, Terri; Koenigstorfer, Joerg - In: Nonprofit management & leadership 35 (2025) 3, pp. 663-675

Persistent link: https://www.econbiz.de/10015359189

An adaptation of Random Forest to estimate convex non-parametric production technologies : an empirical illustration of efficiency measurement in education

España, Victor J.; Aparicio, Juan; Barber, Xavier - In: International transactions in operational research : a … 32 (2025) 5, pp. 2523-2546

Persistent link: https://www.econbiz.de/10015375682

A hybrid multi-objective optimization approach with NSGA-II for feature selection

Vijai, Praveen; Bagavathi Sivakumar P. - 2025

Gain, Random Forest, and Relief F-based approach. We integrate the strengths of filter and wrapper methodologies to enhance … the efficacy of addressing feature selection. The information gain, random forest, and relief F-based approach are used to …

Persistent link: https://www.econbiz.de/10015420190