Ripple Down Rules The Alternative to Machine Learning 1st Edition Paul Crompton Byeong Ho Kong 1000363686 9781000363685

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Product details:

• ISBN 10: 1000363686
• ISBN 13: 9781000363685
• Author: Paul Crompton Byeong Ho Kong

Machine learning algorithms hold extraordinary promise, but the reality is that their success depends entirely on the suitability of the data available. This book is about Ripple-Down Rules (RDR), an alternative manual technique for rapidly building AI systems. With a human in the loop, RDR is much better able to deal with the limitations of data. Ripple-Down Rules: The Alternative to Machine Learning starts by reviewing the problems with data quality and the problems with conventional approaches to incorporating expert human knowledge into AI systems. It suggests that problems with knowledge acquisition arise because of mistaken philosophical assumptions about knowledge. It argues people never really explain how they reach a conclusion, rather they justify their conclusion by differentiating between cases in a context. RDR is based on this more situated understanding of knowledge. The central features of a RDR approach are explained, and detailed worked examples are presented for different types of RDR, based on freely available software developed for this book. The examples ensure developers have a clear idea of the simple yet counter-intuitive RDR algorithms to easily build their own RDR systems.

Table of contents:

Chapter 1: Problems with Machine Learning and Knowledge Acquisition

Chapter 2: Philosophical Issues in Knowledge Acquisition

Chapter 3: Ripple-Down Rule Overview

Chapter 4: Introduction to Excel_RDR

Chapter 5: Single Classification Example

Chapter 6: Multiple Classification Example

Chapter 7: General Ripple-Down Rules (GRDR)

Chapter 8: Implementation and Deployment of an RDR-Based System

Chapter 9: RDR and Machine Learning

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