Principles Data Mining by Bramer Max (40 results)
Language: English
Published by Springer 2016
Series: Undergraduate Topics in Computer Science, Book 49 of 99. Book 49 of 99 - Undergraduate Topics in Computer Science
- Softcover
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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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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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Paperback. 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 mini…ng 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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Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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Paperback. Condition: New.
Language: English
Published by Springer 2016
Series: Undergraduate Topics in Computer Science, Book 49 of 99. Book 49 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Condition: New.
Language: English
Published by Springer 2016
Series: Undergraduate Topics in Computer Science, Book 49 of 99. Book 49 of 99 - Undergraduate Topics in Computer Science
- Softcover
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Condition: New.
Language: English
Published by Springer 2016
Series: Undergraduate Topics in Computer Science, Book 49 of 99. Book 49 of 99 - Undergraduate Topics in Computer Science
- Softcover
Seller: Biblios, frankfurt am main, GermanyBiblios
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Paperback. Condition: Brand New. 4th edition. 571 pages. 9.00x6.00x1.25 inches. In Stock.
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Paperback. 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 req…uested 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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Paperback. 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 mini…ng 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.
