Data mining :: practical machine learning tools and techniques /
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 o...
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| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Burlington, MA :
Morgan Kaufmann,
©2011.
|
| Ausgabe: | 3rd ed. |
| Schriftenreihe: | Morgan Kaufmann series in data management systems.
|
| Schlagworte: | |
| Online-Zugang: | Volltext Volltext |
| Zusammenfassung: | 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. |
| Beschreibung: | 1 online resource (xxxiii, 629 pages) : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9780123748560 0123748569 9780080890364 0080890369 |
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| 245 | 1 | 0 | |a Data mining : |b practical machine learning tools and techniques / |c Ian H. Witten, Eibe Frank, Mark A. Hall. |
| 250 | |a 3rd ed. | ||
| 260 | |a Burlington, MA : |b Morgan Kaufmann, |c ©2011. | ||
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| 588 | 0 | |a Print version record. | |
| 520 | |a 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. | ||
| 505 | 0 | |a 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. | |
| 504 | |a Includes bibliographical references and index. | ||
| 650 | 0 | |a Data mining. |0 http://id.loc.gov/authorities/subjects/sh97002073 | |
| 650 | 1 | 2 | |a Data Mining |
| 650 | 6 | |a Exploration de données (Informatique) | |
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| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a Data mining. |2 nli | |
| 650 | 7 | |a Machine learning. |2 nli | |
| 650 | 7 | |a Data mining. |2 sao | |
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| 655 | 7 | |a dissertations. |2 aat | |
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| 655 | 7 | |a Thèses et écrits académiques. |2 rvmgf | |
| 700 | 1 | |a Frank, Eibe, |e author. |0 http://id.loc.gov/authorities/names/n99831139 | |
| 700 | 1 | |a Hall, Mark A. |q (Mark Andrew), |e author. |0 http://id.loc.gov/authorities/names/no2011034315 | |
| 758 | |i has work: |a Data mining (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGP6KVKbcX4BhdymJk7Dmb |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Witten, I.H. (Ian H.). |t Data mining. |b 3rd ed. |d Burlington, MA : Morgan Kaufmann, ©2011 |z 9780123748560 |w (DLC) 2010039827 |w (OCoLC)262433473 |
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| adam_text | |
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| author | Witten, I. H. (Ian H.) Frank, Eibe Hall, Mark A. (Mark Andrew) |
| author_GND | http://id.loc.gov/authorities/names/n80102097 http://id.loc.gov/authorities/names/n99831139 http://id.loc.gov/authorities/names/no2011034315 |
| author_facet | Witten, I. H. (Ian H.) Frank, Eibe Hall, Mark A. (Mark Andrew) |
| author_role | aut aut aut |
| author_sort | Witten, I. H. |
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| 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. |
| ctrlnum | (OCoLC)706802868 |
| dewey-full | 006.3/12 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/12 |
| dewey-search | 006.3/12 |
| dewey-sort | 16.3 212 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| edition | 3rd ed. |
| format | Electronic eBook |
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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. 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| genre | Internet Resources. dissertations. aat Academic theses fast Academic theses. lcgft http://id.loc.gov/authorities/genreForms/gf2014026039 Thèses et écrits académiques. rvmgf |
| genre_facet | Internet Resources. dissertations. Academic theses Academic theses. Thèses et écrits académiques. |
| id | ZDB-4-EBA-ocn706802868 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:17:44Z |
| institution | BVB |
| isbn | 9780123748560 0123748569 9780080890364 0080890369 |
| language | English |
| lccn | 2010039827 |
| oclc_num | 706802868 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (xxxiii, 629 pages) : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | Morgan Kaufmann, |
| record_format | marc |
| series | Morgan Kaufmann series in data management systems. |
| series2 | [Morgan Kaufmann series in data management systems] |
| spelling | Witten, I. H. (Ian H.), author. https://id.oclc.org/worldcat/entity/E39PBJgtcvTkCHwPWXvxbwgHYP http://id.loc.gov/authorities/names/n80102097 Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall. 3rd ed. Burlington, MA : Morgan Kaufmann, ©2011. 1 online resource (xxxiii, 629 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier data file rda [Morgan Kaufmann series in data management systems] Print version record. 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. 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. Includes bibliographical references and index. Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Data Mining Exploration de données (Informatique) COMPUTERS Database Management Data Mining. bisacsh Computers and IT. eflch Data mining fast Data mining. nli Machine learning. nli Data mining. sao Internet Resources. dissertations. aat Academic theses fast Academic theses. lcgft http://id.loc.gov/authorities/genreForms/gf2014026039 Thèses et écrits académiques. rvmgf Frank, Eibe, author. http://id.loc.gov/authorities/names/n99831139 Hall, Mark A. (Mark Andrew), author. http://id.loc.gov/authorities/names/no2011034315 has work: Data mining (Text) https://id.oclc.org/worldcat/entity/E39PCGP6KVKbcX4BhdymJk7Dmb https://id.oclc.org/worldcat/ontology/hasWork Print version: Witten, I.H. (Ian H.). Data mining. 3rd ed. Burlington, MA : Morgan Kaufmann, ©2011 9780123748560 (DLC) 2010039827 (OCoLC)262433473 Morgan Kaufmann series in data management systems. http://id.loc.gov/authorities/names/n90627178 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=351343 Volltext FWS01 ZDB-4-EBA FWS_PDA_EBA https://www.sciencedirect.com/science/book/9780123748560 Volltext |
| spellingShingle | Witten, I. H. (Ian H.) Frank, Eibe Hall, Mark A. (Mark Andrew) Data mining : practical machine learning tools and techniques / Morgan Kaufmann series in data management systems. 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. Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Data Mining Exploration de données (Informatique) COMPUTERS Database Management Data Mining. bisacsh Computers and IT. eflch Data mining fast Data mining. nli Machine learning. nli Data mining. sao |
| subject_GND | http://id.loc.gov/authorities/subjects/sh97002073 http://id.loc.gov/authorities/genreForms/gf2014026039 |
| title | Data mining : practical machine learning tools and techniques / |
| title_auth | Data mining : practical machine learning tools and techniques / |
| title_exact_search | Data mining : practical machine learning tools and techniques / |
| title_full | Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall. |
| title_fullStr | Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall. |
| title_full_unstemmed | Data mining : practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall. |
| title_short | Data mining : |
| title_sort | data mining practical machine learning tools and techniques |
| title_sub | practical machine learning tools and techniques / |
| topic | Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Data Mining Exploration de données (Informatique) COMPUTERS Database Management Data Mining. bisacsh Computers and IT. eflch Data mining fast Data mining. nli Machine learning. nli Data mining. sao |
| topic_facet | Data mining. Data Mining Exploration de données (Informatique) COMPUTERS Database Management Data Mining. Computers and IT. Data mining Machine learning. Internet Resources. dissertations. Academic theses Academic theses. Thèses et écrits académiques. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=351343 https://www.sciencedirect.com/science/book/9780123748560 |
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