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Cover: 9780128042915 | Data Mining | Practical Machine Learning Tools and Techniques | Buch
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Data Mining
Practical Machine Learning Tools and Techniques
Taschenbuch von Ian Witten (u. a.)
Sprache: Englisch

61,80 €*

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Beschreibung
Rev. edition of: Data mining: practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall. c2013.
Rev. edition of: Data mining: practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall. c2013.
Über den Autor
Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from Essex University, England. He is a fellow of the ACM and of the Royal Society of New Zealand. He has published widely on digital libraries, machine learning, text compression, hypertext, speech synthesis and signal processing, and computer typography.
Inhaltsverzeichnis

Part I: Introduction to data mining 1. What's it all about? 2. Input: Concepts, instances, attributes 3. Output: Knowledge representation 4. Algorithms: The basic methods 5. Credibility: Evaluating what's been learned

Part II. More advanced machine learning schemes 6. Trees and rules 7. Extending instance-based and linear models 8. Data transformations 9. Probabilistic methods 10. Deep learning 11. Beyond supervised and unsupervised learning 12. Ensemble learning 13. Moving on: applications and beyond

Details
Erscheinungsjahr: 2017
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9780128042915
ISBN-10: 0128042915
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Witten, Ian
Frank, Eibe
Hall, Mark A.
Pal, Christopher J.
Auflage: 4. Auflage
Hersteller: Elsevier LTD
Morgan Kaufmann
Maße: 233 x 191 x 32 mm
Von/Mit: Ian Witten (u. a.)
Erscheinungsdatum: 02.01.2017
Gewicht: 1,305 kg
Artikel-ID: 108187567
Über den Autor
Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from Essex University, England. He is a fellow of the ACM and of the Royal Society of New Zealand. He has published widely on digital libraries, machine learning, text compression, hypertext, speech synthesis and signal processing, and computer typography.
Inhaltsverzeichnis

Part I: Introduction to data mining 1. What's it all about? 2. Input: Concepts, instances, attributes 3. Output: Knowledge representation 4. Algorithms: The basic methods 5. Credibility: Evaluating what's been learned

Part II. More advanced machine learning schemes 6. Trees and rules 7. Extending instance-based and linear models 8. Data transformations 9. Probabilistic methods 10. Deep learning 11. Beyond supervised and unsupervised learning 12. Ensemble learning 13. Moving on: applications and beyond

Details
Erscheinungsjahr: 2017
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Kartoniert / Broschiert
ISBN-13: 9780128042915
ISBN-10: 0128042915
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Witten, Ian
Frank, Eibe
Hall, Mark A.
Pal, Christopher J.
Auflage: 4. Auflage
Hersteller: Elsevier LTD
Morgan Kaufmann
Maße: 233 x 191 x 32 mm
Von/Mit: Ian Witten (u. a.)
Erscheinungsdatum: 02.01.2017
Gewicht: 1,305 kg
Artikel-ID: 108187567
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