Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 168,40
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. In.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 168,40
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New. In.
Edité par Springer International Publishing, 2022
ISBN 10 : 3030755231 ISBN 13 : 9783030755232
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 171,19
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierTaschenbuch. 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.
Edité par Springer International Publishing, 2021
ISBN 10 : 3030755207 ISBN 13 : 9783030755201
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
EUR 171,19
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierBuch. 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.
Edité par Springer International Publishing, Springer International Publishing Jun 2022, 2022
ISBN 10 : 3030755231 ISBN 13 : 9783030755232
Langue: anglais
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
EUR 171,19
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierTaschenbuch. 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.
Edité par Springer International Publishing, Springer International Publishing Jun 2021, 2021
ISBN 10 : 3030755207 ISBN 13 : 9783030755201
Langue: anglais
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
EUR 171,19
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierBuch. 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.
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
EUR 168,38
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
EUR 184,13
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : New.
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 247,66
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierHardcover. Etat : Brand New. 186 pages. 9.25x6.10x0.50 inches. In Stock.
Edité par Springer International Publishing, 2021
ISBN 10 : 3030755207 ISBN 13 : 9783030755201
Langue: anglais
Vendeur : moluna, Greven, Allemagne
EUR 144,94
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierGebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and explainableProvides the main idea of the explainable recommenders outlined within the background of neuro-fuzzy systems.
Edité par Springer, Berlin|Springer International Publishing|Springer, 2022
ISBN 10 : 3030755231 ISBN 13 : 9783030755232
Langue: anglais
Vendeur : moluna, Greven, Allemagne
EUR 144,94
Autre deviseQuantité disponible : Plus de 20 disponibles
Ajouter au panierEtat : 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.
Edité par Springer International Publishing Jun 2022, 2022
ISBN 10 : 3030755231 ISBN 13 : 9783030755232
Langue: anglais
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
EUR 171,19
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierTaschenbuch. 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.
Edité par Springer International Publishing Jun 2021, 2021
ISBN 10 : 3030755207 ISBN 13 : 9783030755201
Langue: anglais
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
EUR 171,19
Autre deviseQuantité disponible : 2 disponible(s)
Ajouter au panierBuch. 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.