Screen LibraryMachine learning and data mining : introduction to principles and algorithms /
Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and development...
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| Main Authors: | |
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| Published: |
Horwood Publishing,
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| Publisher Address: | Chichester, England : |
| Publication Dates: | 2007. |
| Literature type: | eBook |
| Language: | English |
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| Online Access: |
http://www.sciencedirect.com/science/book/9781904275213 |
| Summary: |
Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining. Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data miningA valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. |
| Carrier Form: | 1 online resource (475 pages) : illustrations |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9780857099440 0857099442 |
| Index Number: | Q325 |
| CLC: | TP181 |
| Contents: | Introduction -- Learning and intelligence -- Machine learning basics -- Knowledge representation -- Learning as search -- Attribute quality matters -- Data preprocessing -- Constructive induction -- Symbolic learning -- Statistical learning -- Artificial neural networks -- Cluster analysis -- Learning theory -- Computational learning theory -- Definitions of some lesser known terms. |