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Principles of Data Mining (Paperback, 4th ed. 2020)
Loot Price: R1,166
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Principles of Data Mining (Paperback, 4th ed. 2020)
Series: Undergraduate Topics in Computer Science
Expected to ship within 9 - 15 working days
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This book explains and explores the principal techniques of Data
Mining, the automatic extraction of implicit and potentially useful
information from data, which is increasingly used in commercial,
scientific and other application areas. It focuses on
classification, association rule mining and clustering. Each topic
is clearly explained, with a focus on algorithms not mathematical
formalism, and is illustrated by detailed worked examples. The book
is written for readers without a strong background in mathematics
or statistics and any formulae used are explained in detail. It can
be used as a textbook to support courses at undergraduate or
postgraduate levels in a wide range of subjects including Computer
Science, Business Studies, Marketing, Artificial Intelligence,
Bioinformatics and Forensic Science. As an aid to self-study, it
aims to help general readers develop the necessary understanding of
what is inside the 'black box' so they can use commercial data
mining packages discriminatingly, as well as enabling advanced
readers or academic researchers to understand or contribute to
future technical advances in the field. Each chapter has practical
exercises to enable readers to check their progress. A full
glossary of technical terms used is included. Principles of Data
Mining includes descriptions of algorithms for classifying
streaming data, both stationary data, where the underlying model is
fixed, and data that is time-dependent, where the underlying model
changes from time to time - a phenomenon known as concept drift.
The expanded fourth edition gives a detailed description of a
feed-forward neural network with backpropagation and shows how it
can be used for classification.
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