Description: Explainable Artificial Intelligence Based on Neuro-fuzzy Modeling With Applications in Finance, Paperback by Rutkowski, Tom, ISBN 3030755231, ISBN-13 9783030755232, Like New Used, Free shipping in the US Th 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, ., 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 th 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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Book Title: Explainable Artificial Intelligence Based on Neuro-fuzzy Modeling
Number of Pages: Xix, 167 Pages
Language: English
Publication Name: Explainable Artificial Intelligence Based on Neuro-Fuzzy Modeling with Applications in Finance
Publisher: Springer International Publishing A&G
Subject: Engineering (General), Intelligence (Ai) & Semantics, Finance / General, Data Processing
Publication Year: 2022
Type: Textbook
Item Weight: 10.4 Oz
Author: Tom Rutkowski
Item Length: 9.3 in
Subject Area: Computers, Technology & Engineering, Business & Economics
Series: Studies in Computational Intelligence Ser.
Item Width: 6.1 in
Format: Trade Paperback
