Significance, relevance and explainability in the machine learning age : an econometrics and financial data science perspective
Andreas G.F. Hoepner, David McMillan, Andrew Vivian and Chardin Wese Simen
| Year of publication: |
2021
|
|---|---|
| Authors: | Hoepner, Andreas G. F. ; McMillan, David G. ; Vivian, Andrew ; Wese Simen, Chardin |
| Subject: | explainability | explainable artificial intelligence (xai) | neural networks | regressions | relevance | significance | Künstliche Intelligenz | Artificial intelligence | Neuronale Netze | Neural networks | Regressionsanalyse | Regression analysis | Ökonometrie | Econometrics | Prognoseverfahren | Forecasting model |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1080/1351847X.2020.1847725 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://ebvufind01.dmz1.zbw.eu/10012424925