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

Rutkowski, Tom

ISBN 10: 3030755231 ISBN 13: 9783030755232

Editorial: Springer, 2022

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2022. 1st ed. 2021. paperback. . . . . . Books ship from the US and Ireland. N� de ref. del art�culo V9783030755232

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Sinopsis:

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.

Acerca del autor: Charlotte y Peter Fiell son dos autoridades en historia, teor�a y cr�tica del dise�o y han escrito m�s de sesenta libros sobre la materia, muchos de los cuales se han convertido en �xitos de ventas. Tambi�n han impartido conferencias y cursos como profesores invitados, han comisariado exposiciones y asesorado a fabricantes, museos, salas de subastas y grandes coleccionistas privados de todo el mundo. Los Fiell han escrito numerosos libros para TASCHEN, entre los que se incluyen 1000 Chairs, Dise�o del siglo XX, El dise�o industrial de la A a la Z, Scandinavian Design y Dise�o del siglo XXI.

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T�tulo: Explainable Artificial Intelligence Based on...
Editorial: Springer
A�o de publicaci�n: 2022
Encuadernaci�n: Encuadernaci�n de tapa blanda
Condici�n: New

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

Rutkowski, Tom

Publicado por Springer, Berlin|Springer International Publishing|Springer, 2022

ISBN 10: 3030755231 ISBN 13: 9783030755232

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Condici�n: 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 ref. del art�culo: 600116332

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

Tom Rutkowski

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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

Publicado por 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

Publicado por Springer International Publishing, Springer International Publishing Jun 2022, 2022

ISBN 10: 3030755231 ISBN 13: 9783030755232

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Taschenbuch. Condici�n: 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 ref. del art�culo: 9783030755232

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

Tom Rutkowski

Publicado por Springer International Publishing, 2022

ISBN 10: 3030755231 ISBN 13: 9783030755232

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Librería: AHA-BUCH GmbH, Einbeck, Alemania

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Taschenbuch. Condici�n: 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 ref. del art�culo: 9783030755232

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

Tom Rutkowski

Publicado por Springer International Publishing Jun 2022, 2022

ISBN 10: 3030755231 ISBN 13: 9783030755232

Nuevo Taschenbuch

Impresi�n bajo demanda

Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: 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 ref. del art�culo: 9783030755232

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