Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance by Tom Rutkowski

Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance by Tom Rutkowski

The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainable. The vast majority of AI models work like black box models. However, in many applications, e.g., medical diagnosis or venture capital investment recommendations, it is essential to explain the rationale behind AI systems decisions or recommendations. Therefore, the development of artificial intelligence cannot ignore the need for interpretable, transparent, and explainable models. First, the main idea of the explainable recommenders is outlined within the background of neuro-fuzzy systems. In turn, various novel recommenders are proposed, each characterized by achieving high accuracy with a reasonable number of interpretable fuzzy rules. The main part of the book is devoted to a very challenging problem of stock market recommendations. An original concept of the explainable recommender, based on patterns from previous transactions, is developed; it recommends stocks that fit the strategy of investors, and its recommendations are explainable for investment advisers.

SKU	Nicht verfügbar
ISBN 13	9783030755232
ISBN 10	3030755231
Titel	Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance
Autor	Tom Rutkowski
Serie	Studies In Computational Intelligence
Buchzustand	Nicht verfügbar
Bindungsart	Paperback
Verlag	Springer Nature Switzerland AG
Erscheinungsjahr	2022-06-09
Seitenanzahl	167
Hinweis auf dem Einband	Die Abbildung des Buches dient nur Illustrationszwecken, die tatsächliche Bindung, das Cover und die Auflage können sich davon unterscheiden.
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