Interpretable Machine Learning : Shapley Values (Seminar Slides)

Machine learning (ML) algorithms utilize the power of computers to solve tasks that are beyond the grasp of classical statistical methods. However, ML is often perceived as a black-box, hindering its adoption. This seminar demonstrates the use of Shapley values to interpret the outputs of ML models. With the help of interpretability methods, ML is becoming the primary tool of scientific discovery, through induction as well as abduction

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Year of publication:	2020
Authors:	Lopez de Prado, Marcos
Publisher:	[2020]: [S.l.] : SSRN
Subject:	Theorie \| Theory \| Künstliche Intelligenz \| Artificial intelligence \| Shapley-Wert \| Shapley value \| Kooperatives Spiel \| Cooperative game

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Extent:	1 Online-Ressource (24 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 27, 2020 erstellt
Other identifiers:	10.2139/ssrn.3637020 [DOI]
Classification:	G0 - Financial Economics. General ; G1 - General Financial Markets ; G2 - Financial Institutions and Services ; G15 - International Financial Markets ; G24 - Investment Banking; Venture Capital; Brokerage ; E44 - Financial Markets and the Macroeconomy
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012829873