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Springer Rule Extraction from Support Vector Machines - Studies 80

Name: Rule Extraction from Support Vector Machines - Studies 80
Brand: Springer
Price: 42.76 GBP
Availability: InStock

3187102

AI & Machine Learning

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Description

Support vector machines (SVMs) are among the most active research areas in machine learning, delivering strong performance across text and image classification tasks. However, SVMs present a significant challenge: their learning capability comes with an inherent inability to explain their decision-making process in comprehensible terms. This book addresses that critical gap by exploring methods for extracting symbolic rules from SVMs, much like approaches developed for neural networks. Rule extraction is essential for SVMs to achieve wider acceptance in domains where interpretability and explainability are paramount. This volume, part of Springer's Studies in Computational Intelligence series (volume 80), provides comprehensive coverage of techniques and approaches for transforming opaque SVM models into transparent, human-readable rules. It serves researchers, practitioners, and students working in machine learning who need both the power of support vector machines and the ability to understand and communicate how those models reach their conclusions.

Key Features

Addresses the interpretability challenge inherent in support vector machines (SVMs) by presenting systematic rule extraction methods.

Explores symbolic rule extraction techniques adapted from neural network research to make SVM decisions transparent and comprehensible.

Part of Springer's Studies in Computational Intelligence series, volume 80, providing authoritative academic content on machine learning.

Covers practical applications of rule extraction for SVMs in text classification, image classification, and other real-world domains.

Bridges the gap between SVM performance advantages and the need for explainable artificial intelligence in modern applications.

Product Specifications

Brand: Springer
Model: 3187102
Format: hardcover
ASIN: 3540753893
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 04 January 2008
Listed Since: 17 September 2007

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Springer Rule Extraction from Support Vector Machines - Studies 80

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Springer Rule Extraction from Support Vector Machines - Studies 80

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