| Edition |
3rd ed. |
| Description |
1 online resource (xxxiii, 629 pages) : illustrations |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
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data file rda |
| Series |
[Morgan Kaufmann series in data management systems] |
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Morgan Kaufmann series in data management systems.
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| Note |
Print version record. |
| Summary |
Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. |
| Contents |
What's it all about? -- Input : concepts, instances, and attributes -- Output : knowledge representation -- Algorithms : the basic methods -- Credibility : evaluating what's been learned -- Implementations : real machine learning schemes -- Data transformation -- Ensemble learning -- Moving on : applications and beyond -- Introduction to Weka -- The explorer -- The knowledge flow interface -- The experimenter -- The command-line interface -- Embedded machine learning -- Writing new learning schemes -- Tutorial exercises for the weka explorer. |
| Bibliography |
Includes bibliographical references and index. |
| Subject |
Data mining.
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Data Mining |
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Exploration de données (Informatique)
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COMPUTERS -- Database Management -- Data Mining.
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Computers and IT.
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Data mining
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Data mining.
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Machine learning.
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Data mining.
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| Genre/Form |
Internet Resources.
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dissertations.
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Academic theses
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Academic theses.
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Thèses et écrits académiques.
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| Added Author |
Frank, Eibe, author.
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Hall, Mark A. (Mark Andrew), author.
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| Other Form: |
Print version: Witten, I.H. (Ian H.). Data mining. 3rd ed. Burlington, MA : Morgan Kaufmann, ©2011 9780123748560 (DLC) 2010039827 (OCoLC)262433473 |
| ISBN |
9780123748560 (electronic bk.) |
|
0123748569 (electronic bk.) |
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9780080890364 (electronic bk.) |
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0080890369 (electronic bk.) |
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9780123748560 (pbk.) |
|
0123748569 (pbk.) |
| Standard No. |
9780123748560 |
|
9786612953880 |
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AU@ 000047983227 |
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AU@ 000051603496 |
|
CHNEW 000720586 |
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CHNEW 001010041 |
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DEBBG BV039829358 |
|
DEBBG BV040900672 |
|
DEBBG BV042314259 |
|
DEBSZ 360078508 |
|
DEBSZ 378275755 |
|
DEBSZ 381367002 |
|
DEBSZ 405358059 |
|
DEBSZ 43418358X |
|
DEBSZ 481266623 |
|
DKDLA 820010-katalog:ssj0000468262 |
|
NZ1 13761657 |
|
UKMGB 017585698 |
|
