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Principles Data Mining by Bramer Max (40 results)
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Paperback. Condition: Fair. No Jacket. Former library book; Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.
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Soft cover. Condition: New. ISBN:9788184891669,Territorial restriction maybe printed on the book. This is an Int'l edition, ISBN and cover may differ from US edition, Contents same as US edition.
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Condition: As New. Unread book in perfect condition.
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Principles of Data Mining (Undergraduate Topics in Computer Science)
Seller: Books From California, Simi Valley, CA, U.S.A.
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paperback. Condition: Good. The binding is creased. The copy shows minor external wear, but is in otherwise clean condition.
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Principles of Data Mining (Undergraduate Topics in Computer Science)
Seller: Books From California, Simi Valley, CA, U.S.A.
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paperback. Condition: Very Good. Cover and edges may have some wear.
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Principles of Data Mining, Second Edition (Undergraduate Topics in Computer Science)
Language: English
Published by Springer (edition 2nd ed. 2013), 2013
ISBN 10: 1447148835 ISBN 13: 9781447148838
Paperback. Condition: Fair. 2nd ed. 2013. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.
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Principles of Data Mining
Language: English
Published by Springer London Ltd, GB, 2020
ISBN 10: 1447174925 ISBN 13: 9781447174929
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Add to basketPaperback. Condition: New. 4th ed. 2020. 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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Principles of Data Mining (Undergraduate Topics in Computer Science)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Principles of Data Mining
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. pp. 16.
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Principles of Data Mining
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Condition: New. pp. 16.
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Principles of Data Mining
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Principles of Data Mining
Language: English
Published by Springer-Nature New York Inc, 2020
ISBN 10: 1447174925 ISBN 13: 9781447174929
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Add to basketPaperback. Condition: Brand New. 4th edition. 571 pages. 9.00x6.00x1.25 inches. In Stock.
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International EditionUS$ 109.40
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Add to basketPaperback. Condition: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Kartoniert / Broschiert. Condition: New. Presents the principal techniques of data mining with particular emphasis on explaining and motivating the techniques usedEach topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked ex.
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Principles of Data Mining
Language: English
Published by Springer London Ltd, GB, 2020
ISBN 10: 1447174925 ISBN 13: 9781447174929
US$ 39.90
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Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback. Condition: New. 4th ed. 2020. 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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Taschenbuch. Condition: Neu. Principles of Data Mining | Max Bramer | Taschenbuch | Undergraduate Topics in Computer Science | xvi | Englisch | 2020 | Springer | EAN 9781447174929 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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, bothstationary data, where the underlying model is fixed, and data that istime-dependent, where the underlying model changes from time to time - a phenomenon known asconcept 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.
