Data mining [[electronic resource] ] : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank, Mark A. Hall
| Data mining [[electronic resource] ] : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank, Mark A. Hall |
| Autore | Witten I. H (Ian H.) |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Amsterdam, : Elsevier/Morgan Kaufmann, 2011 |
| Descrizione fisica | 1 online resource (665 p.) : ill |
| Disciplina | 006.3/12 |
| Altri autori (Persone) |
FrankEibe
HallMark A |
| Collana | The Morgan Kaufmann Series in Data Management Systems |
| Soggetto topico | Data mining |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-282-95388-5
9786612953880 0-08-089036-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I. Machine learning tools and techniques: 1. What's it all about?; 2. Input: concepts, instances, and attributes; 3. Output: knowledge representation; 4. Algorithms: the basic methods; 5. Credibility: evaluating what's been learned -- Part II. Advanced Data Mining: 6. Implementations: real machine learning schemes; 7. Data transformation; 8. Ensemble learning; 9. Moving on: applications and beyond -- Part III. The Weka Data MiningWorkbench: 10. Introduction to Weka; 11. The explorer -- 12. The knowledge flow interface; 13. The experimenter; 14 The command-line interface; 15. Embedded machine learning; 16. Writing new learning schemes; 17. Tutorial exercises for the weka explorer. |
| Record Nr. | UNINA-9910459549103321 |
Witten I. H (Ian H.)
|
||
| Amsterdam, : Elsevier/Morgan Kaufmann, 2011 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data mining [[electronic resource] ] : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank, Mark A. Hall
| Data mining [[electronic resource] ] : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank, Mark A. Hall |
| Autore | Witten I. H (Ian H.) |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Amsterdam, : Elsevier/Morgan Kaufmann, 2011 |
| Descrizione fisica | 1 online resource (665 p.) : ill |
| Disciplina | 006.3/12 |
| Altri autori (Persone) |
FrankEibe
HallMark A |
| Collana | The Morgan Kaufmann Series in Data Management Systems |
| Soggetto topico | Data mining |
| ISBN |
1-282-95388-5
9786612953880 0-08-089036-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I. Machine learning tools and techniques: 1. What's it all about?; 2. Input: concepts, instances, and attributes; 3. Output: knowledge representation; 4. Algorithms: the basic methods; 5. Credibility: evaluating what's been learned -- Part II. Advanced Data Mining: 6. Implementations: real machine learning schemes; 7. Data transformation; 8. Ensemble learning; 9. Moving on: applications and beyond -- Part III. The Weka Data MiningWorkbench: 10. Introduction to Weka; 11. The explorer -- 12. The knowledge flow interface; 13. The experimenter; 14 The command-line interface; 15. Embedded machine learning; 16. Writing new learning schemes; 17. Tutorial exercises for the weka explorer. |
| Record Nr. | UNINA-9910785305703321 |
Witten I. H (Ian H.)
|
||
| Amsterdam, : Elsevier/Morgan Kaufmann, 2011 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data mining : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank, Mark A. Hall
| Data mining : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank, Mark A. Hall |
| Autore | Witten I. H (Ian H.) |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Amsterdam, : Elsevier/Morgan Kaufmann, 2011 |
| Descrizione fisica | 1 online resource (665 p.) : ill |
| Disciplina |
006.3/12
006.312 |
| Altri autori (Persone) |
FrankEibe
HallMark A |
| Collana | The Morgan Kaufmann Series in Data Management Systems |
| Soggetto topico | Data mining |
| ISBN |
9786612953880
9781282953888 1282953885 9780080890364 0080890369 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I. Machine learning tools and techniques: 1. What's it all about?; 2. Input: concepts, instances, and attributes; 3. Output: knowledge representation; 4. Algorithms: the basic methods; 5. Credibility: evaluating what's been learned -- Part II. Advanced Data Mining: 6. Implementations: real machine learning schemes; 7. Data transformation; 8. Ensemble learning; 9. Moving on: applications and beyond -- Part III. The Weka Data MiningWorkbench: 10. Introduction to Weka; 11. The explorer -- 12. The knowledge flow interface; 13. The experimenter; 14 The command-line interface; 15. Embedded machine learning; 16. Writing new learning schemes; 17. Tutorial exercises for the weka explorer. |
| Record Nr. | UNINA-9911100306303321 |
Witten I. H (Ian H.)
|
||
| Amsterdam, : Elsevier/Morgan Kaufmann, 2011 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data mining : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank, Mark A. Hall
| Data mining : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank, Mark A. Hall |
| Autore | Witten I. H (Ian H.) |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Elsevier Science & Technology, 2011 |
| Descrizione fisica | 1 online resource (665 p.) : ill |
| Disciplina |
006.3/12
006.312 |
| Altri autori (Persone) |
FrankEibe
HallMark A |
| Collana | The Morgan Kaufmann Series in Data Management Systems |
| Soggetto topico | Data mining |
| ISBN |
9786612953880
9781282953888 1282953885 9780080890364 0080890369 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I. Machine learning tools and techniques: 1. What's it all about?; 2. Input: concepts, instances, and attributes; 3. Output: knowledge representation; 4. Algorithms: the basic methods; 5. Credibility: evaluating what's been learned -- Part II. Advanced Data Mining: 6. Implementations: real machine learning schemes; 7. Data transformation; 8. Ensemble learning; 9. Moving on: applications and beyond -- Part III. The Weka Data MiningWorkbench: 10. Introduction to Weka; 11. The explorer -- 12. The knowledge flow interface; 13. The experimenter; 14 The command-line interface; 15. Embedded machine learning; 16. Writing new learning schemes; 17. Tutorial exercises for the weka explorer. |
| Record Nr. | UNINA-9911139126803321 |
Witten I. H (Ian H.)
|
||
| Elsevier Science & Technology, 2011 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data mining [[electronic resource] ] : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank
| Data mining [[electronic resource] ] : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank |
| Autore | Witten I. H (Ian H.) |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Amsterdam ; ; Boston, MA, : Morgan Kaufman, 2005 |
| Descrizione fisica | 1 online resource (xxxi, 524 p.) : ill |
| Disciplina | 006.3 |
| Altri autori (Persone) | FrankEibe |
| Collana | Morgan Kaufmann series in data management systems |
| Soggetto topico |
Data mining
Database searching |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9786611008062
0-08-047702-X 9781423722442 1-281-00806-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | PART I: MACHINE LEARNING TOOLS AND TECHNIQUES; 1 What's it all about?; 2 Input: Concepts, instances, and attributes; 3 Output: Knowledge representation; 4 Algorithms: The basic methods; 5 Credibility: Evaluating what's been learned; 6 Implementations: Real machine learning schemes; 7 Transformations: Engineering the input and output; 8 Moving on: Extensions and applications; PART II: THE WEKA MACHINE LEARNING WORKBENCH; 9 Introduction to Weka; 10 The Explorer; 11 The Knowledge Flow Interface; 12 The Experimenter; 13 The Command-Line Interface; 14 Embedded machine learning; 15 Writing New Learning Schemes; References; Index; About the Authors. |
| Record Nr. | UNINA-9910449698103321 |
Witten I. H (Ian H.)
|
||
| Amsterdam ; ; Boston, MA, : Morgan Kaufman, 2005 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data mining [[electronic resource] ] : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank
| Data mining [[electronic resource] ] : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank |
| Autore | Witten I. H (Ian H.) |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Amsterdam ; ; Boston, MA, : Morgan Kaufman, 2005 |
| Descrizione fisica | 1 online resource (xxxi, 524 p.) : ill |
| Disciplina | 006.3 |
| Altri autori (Persone) | FrankEibe |
| Collana | Morgan Kaufmann series in data management systems |
| Soggetto topico |
Data mining
Database searching |
| ISBN |
9786611008062
0-08-047702-X 9781423722442 1-281-00806-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | PART I: MACHINE LEARNING TOOLS AND TECHNIQUES; 1 What's it all about?; 2 Input: Concepts, instances, and attributes; 3 Output: Knowledge representation; 4 Algorithms: The basic methods; 5 Credibility: Evaluating what's been learned; 6 Implementations: Real machine learning schemes; 7 Transformations: Engineering the input and output; 8 Moving on: Extensions and applications; PART II: THE WEKA MACHINE LEARNING WORKBENCH; 9 Introduction to Weka; 10 The Explorer; 11 The Knowledge Flow Interface; 12 The Experimenter; 13 The Command-Line Interface; 14 Embedded machine learning; 15 Writing New Learning Schemes; References; Index; About the Authors. |
| Record Nr. | UNINA-9910783456403321 |
Witten I. H (Ian H.)
|
||
| Amsterdam ; ; Boston, MA, : Morgan Kaufman, 2005 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data mining : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank
| Data mining : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank |
| Autore | Witten I. H (Ian H.) |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Amsterdam ; ; Boston, MA, : Morgan Kaufman, 2005 |
| Descrizione fisica | 1 online resource (xxxi, 524 p.) : ill |
| Disciplina | 006.3 |
| Altri autori (Persone) | FrankEibe |
| Collana | Morgan Kaufmann series in data management systems |
| Soggetto topico |
Data mining
Database searching |
| ISBN |
9786611008062
0-08-047702-X 9781423722442 1-281-00806-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | PART I: MACHINE LEARNING TOOLS AND TECHNIQUES; 1 What's it all about?; 2 Input: Concepts, instances, and attributes; 3 Output: Knowledge representation; 4 Algorithms: The basic methods; 5 Credibility: Evaluating what's been learned; 6 Implementations: Real machine learning schemes; 7 Transformations: Engineering the input and output; 8 Moving on: Extensions and applications; PART II: THE WEKA MACHINE LEARNING WORKBENCH; 9 Introduction to Weka; 10 The Explorer; 11 The Knowledge Flow Interface; 12 The Experimenter; 13 The Command-Line Interface; 14 Embedded machine learning; 15 Writing New Learning Schemes; References; Index; About the Authors. |
| Record Nr. | UNINA-9911109706003321 |
Witten I. H (Ian H.)
|
||
| Amsterdam ; ; Boston, MA, : Morgan Kaufman, 2005 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data mining : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank
| Data mining : practical machine learning tools and techniques / / Ian H. Witten, Eibe Frank |
| Autore | Witten I. H (Ian H.) |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Amsterdam ; ; Boston, MA, : Morgan Kaufman, 2005 |
| Descrizione fisica | 1 online resource (xxxi, 524 p.) : ill |
| Disciplina | 006.3 |
| Altri autori (Persone) | FrankEibe |
| Collana | Morgan Kaufmann series in data management systems |
| Soggetto topico |
Data mining
Database searching |
| ISBN |
9786611008062
0-08-047702-X 9781423722442 1-281-00806-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | PART I: MACHINE LEARNING TOOLS AND TECHNIQUES; 1 What's it all about?; 2 Input: Concepts, instances, and attributes; 3 Output: Knowledge representation; 4 Algorithms: The basic methods; 5 Credibility: Evaluating what's been learned; 6 Implementations: Real machine learning schemes; 7 Transformations: Engineering the input and output; 8 Moving on: Extensions and applications; PART II: THE WEKA MACHINE LEARNING WORKBENCH; 9 Introduction to Weka; 10 The Explorer; 11 The Knowledge Flow Interface; 12 The Experimenter; 13 The Command-Line Interface; 14 Embedded machine learning; 15 Writing New Learning Schemes; References; Index; About the Authors. |
| Record Nr. | UNINA-9911135660503321 |
Witten I. H (Ian H.)
|
||
| Amsterdam ; ; Boston, MA, : Morgan Kaufman, 2005 | ||
| Lo trovi qui: Univ. Federico II | ||
| ||