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

Rutkowski, Tom

ISBN 10: 3030755231 ISBN 13: 9783030755232

Edit� par Springer, 2022

Neuf(s) Couverture souple

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2022. 1st ed. 2021. paperback. . . . . . Books ship from the US and Ireland. N� de r�f. du vendeur V9783030755232

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Synopsis :

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.

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Titre : Explainable Artificial Intelligence Based on...
�diteur : Springer
Date d'�dition : 2022
Reliure : Couverture souple
Etat : New

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

Rutkowski, Tom

Edit� par Springer, Berlin|Springer International Publishing|Springer, 2022

ISBN 10 : 3030755231 ISBN 13 : 9783030755232

Neuf Couverture souple

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 d. N� de r�f. du vendeur 600116332

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

Tom Rutkowski

Edit� par Springer, 2022

ISBN 10 : 3030755231 ISBN 13 : 9783030755232

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Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance (Studies in Computational Intelligence)

Rutkowski, Tom

Edit� par Springer, 2022

ISBN 10 : 3030755231 ISBN 13 : 9783030755232

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

Tom Rutkowski

Edit� par Springer International Publishing, Springer International Publishing Jun 2022, 2022

ISBN 10 : 3030755231 ISBN 13 : 9783030755232

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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

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Taschenbuch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 188 pp. Englisch. N� de r�f. du vendeur 9783030755232

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

Tom Rutkowski

Edit� par Springer International Publishing, 2022

ISBN 10 : 3030755231 ISBN 13 : 9783030755232

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N� de r�f. du vendeur 9783030755232

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

Tom Rutkowski

Edit� par Springer International Publishing Jun 2022, 2022

ISBN 10 : 3030755231 ISBN 13 : 9783030755232

Neuf Taschenbuch

impression � la demande

Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 188 pp. Englisch. N� de r�f. du vendeur 9783030755232

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