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Springer - Interpretability Issues in Fuzzy Modeling (Vol 128)

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Description

Fuzzy modeling represents one of the most successful outcomes of fuzzy logic, with applications spanning knowledge discovery, automatic classification, long-term prediction, and medical or engineering analysis. While recent research has focused on using model flexibility to achieve high accuracy, this often comes at the expense of model interpretability. This volume from the Studies in Fuzziness and Soft Computing series addresses this imbalance. It revisits the original philosophy of fuzzy sets theory, which was designed to act as a bridge between human understanding and complex data. This book provides essential insights for researchers and professionals looking to balance high-accuracy modeling with the need for transparent, interpretable results.

Key Features

This book is part of the Studies in Fuzziness and Soft Computing series, specifically volume 128.

Published by Springer, this text covers advanced applications in knowledge discovery and automatic classification.

The content explores the balance between high-accuracy fuzzy modeling and the necessity of model interpretability.

It addresses practical applications in medical and engineering analysis through the lens of fuzzy logic.

The research examines how to maintain the original philosophy of fuzzy sets theory to bridge the gap to human understanding.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
16 December 2010
Listed Since
20 September 2010

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No barcode data available

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