Data Mining

Practical Machine Learning Tools and Techniques

Eibe Frank, Ian H. Witten, Mark A. Hall, et al.

EPUB
ca. 55,25
Amazon iTunes Thalia.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi yourbook.shop Kulturkaufhaus ebooks-center.de
* Affiliatelinks/Werbelinks
Hinweis: Affiliatelinks/Werbelinks
Links auf reinlesen.de sind sogenannte Affiliate-Links. Wenn du auf so einen Affiliate-Link klickst und über diesen Link einkaufst, bekommt reinlesen.de von dem betreffenden Online-Shop oder Anbieter eine Provision. Für dich verändert sich der Preis nicht.

Elsevier Science img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Anwendungs-Software

Beschreibung

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, 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. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. - Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects- Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods- Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Weitere Titel von diesem Autor
Weitere Titel in dieser Kategorie
Cover What Is A Database?
Greg Turnquist
Cover Effective Python
Brett Slatkin
Cover Effective Python
Brett Slatkin
Cover Excel's Not Dead
William McBurnie
Cover Async Rust
Caroline Morton
Cover Async Rust
Caroline Morton
Cover Cyber Guardians
William Ubagan

Kundenbewertungen