Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applic...

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Beschreibung

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.




Inhalt
Introduction.- Neuro-Fuzzy Approach and its Application in Recommender Systems.- Novel Explainable Recommenders Based on Neuro-Fuzzy.- Explainable Recommender for Investment Advisers.- Summary and Final Remarks.

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Produktinformationen

Titel
Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance
Autor
EAN
9783030755201
ISBN
3030755207
Format
Fester Einband
Herausgeber
Springer International Publishing
Genre
Allgemeines & Lexika
Anzahl Seiten
188
Gewicht
453g
Größe
H241mm x B160mm x T16mm
Jahr
2021
Untertitel
Englisch
Auflage
1st ed. 2021
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