Estimating non-overfitted convex production technologies : a stochastic machine learning approach
Maria D. Guillen, Vincent Charles, Juan Aparicio
| Year of publication: |
2025
|
|---|---|
| Authors: | Guillen, Maria D. ; Charles, Vincent ; Aparicio, Juan |
| Published in: |
European journal of operational research : EJOR. - Amsterdam [u.a.] : Elsevier, ISSN 0377-2217, ZDB-ID 1501061-2. - Vol. 323.2025, 1 (16.5.), p. 224-240
|
| Subject: | Data Envelopment Analysis | Machine learning | Stochastic gradient boosting | Technical efficiency measurement | Data-Envelopment-Analyse | Data envelopment analysis | Technische Effizienz | Technical efficiency | Künstliche Intelligenz | Artificial intelligence | Theorie | Theory | Stochastischer Prozess | Stochastic process | Produktionsfunktion | Production function | Schätzung | Estimation | Prognoseverfahren | Forecasting model |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.ejor.2024.11.030 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10015415547