Introduction to Machine Learning,
Edition 1
By Yves Kodratoff

Publication Date: 01 Mar 1989

A textbook suitable for undergraduate courses in machine learningand related topics, this book provides a broad survey of the field.Generous exercises and examples give students a firm grasp of theconcepts and techniques of this rapidly developing, challenging subject.

Introduction to Machine Learning synthesizes and clarifiesthe work of leading researchers, much of which is otherwise availableonly in undigested technical reports, journals, and conference proceedings.Beginning with an overview suitable for undergraduate readers, Kodratoffestablishes a theoretical basis for machine learning and describesits technical concepts and major application areas. Relevant logicprogramming examples are given in Prolog.

Introduction to Machine Learning is an accessible and originalintroduction to a significant research area.

About the author
By Yves Kodratoff, University Paris-Sud
Table of Contents
Introduction to Machine Learning

by Yves Kodratoff

9 Learning by Similarity Detection: The "Rational" Approach
    1 Knowledge representation

    2 Description of a rational generalization algorithm

    3 Using axioms and idempotence

    4 A definition of generalization

    5 Use of negative examples

10 Automatic Construction of Taxonomies: Techniques for Clustering
    1 A measure of the amount of information associated with each descriptor

    2 Application of data analysis

    3 Conceptual clustering

11 Debugging and Understanding in Depth: The Learning of Micro-Worlds
    1 Recognition of micro-worlds

    2 Detection of lies

12 Learning by Analogy
    1 A definition of analogy

    2 Winston"s use of analogy

Appendix 1 Equivalence Between Theorems and Clauses
    1 Interpretation

    2 The Herbrand universe of a set of clauses

    3 Semantic trees

    4 Herbrand"s theorem

Appendix 2 Synthesis of Predicates
    1 Motivation: an example of useful synthesis in ML

    2 Synthesis of predicates from input/outputs

    3 Approaches to automatic programming

Appendix 3 Machine Learning in Context
    1 Epistemological reflections on the place of AI in science

    2 Reflections on the social role of ML


Book details
ISBN: 9781558600379
Page Count: 298
Retail Price : £43.99