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

  • Fester Einband
  • 188 Seiten
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The book proposes techniques, with an emphasis on the financial sector, which will make recommendation systems both accurate and ... Weiterlesen
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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.

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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