principles data mining von bramer max (57 Ergebnisse)

Zustand: Gut. Zustand: Gut | Seiten: 343 | Sprache: Englisch | Produktart: Bücher.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 343 | Sprache: Englisch | Produktart: Bücher.

Zustand: Good. 2nd ed. 2013. Ships from the UK. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages.

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1. Ed. kart., 24 cm, 343 S.; die Seiten 6,12,13,14,19,25,27,und 28 sind im Text mit Markerhinterlegungen, meist nur kurz ein oder 2 Worte bzw. ein Satzteil od. web-Hinweis, ansonsten ist das Buch im guten Zustand [auch für das Selbststudium geeignet] // UNDERGRADUATE TOPICS in COMPUTER SCIENCE Undergraduate Topics in Computer Science (UTiCS) delivers high-quality instructional content for undergraduates studying in all areas of computing and information science. From core foundational and theoretical material to final-year topics and applications, UTiCS books take a fresh, concise, and modern approach and are ideal for self-study or for a one- or two-semester course. The texts are all authored by established experts in their fields, reviewed by an international advisory board, and contain numerous examples and problems. Many include fully worked solutions. Max Bramer Principles of Data Mining Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. This book explains and explores the principal techniques of Data Mining: for classification, generation of association rules and clustering. lt is written for readers without a strong background in mathematics or statistics and focuses an detailed examples & explanations of the algorithms given. lt can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help the general reader develop the necessary understanding to use commercial data mining packages discriminatingly, as well as enabling the advanced reader or academic researcher to understand or contribute to future technical advances in the field. Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included. (Deckeltext) Z34532I5 ISBN 9781846287657 Gemäß §19 UStG weist dieser Verkäufer keine Mehrwertsteuer aus (Kleinunternehmerstatus)."Universitätsbibliotheken sowie öffentliche kommunale Bibliotheken können auf Rechnung beliefert werden. Ab 01.01.2023 erfolgt wegen der EPR keine Lieferung nach Österreich mehr; ab dem 01.01.2025 auch keine Lieferung nach Dänemark mehr. Sprache: Deutsch Gewicht in Gramm: 600.

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Paperback. Zustand: New. 4th ed. 2020. This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering.Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail.It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science.As an aid to self-study, it aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field.Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included.Principles of Data Mining includes descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift. The expanded fourth edition gives a detailed description of a feed-forward neural network with backpropagation and shows how it can be used for classification.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering.Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail.It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science.As an aid to self-study, it aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field.Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included.Principles of Data Mining includes descriptions of algorithms for classifying streaming data, bothstationary data, where the underlying model is fixed, and data that istime-dependent, where the underlying model changes from time to time - a phenomenon known asconcept drift. The expanded fourth edition gives a detailed description of a feed-forward neural network with backpropagation and shows how it can be used for classification.

Paperback. Zustand: Very Good. Principles of Data Mining (Undergraduate Topics in Computer Science) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .

Paperback. Zustand: New. 4th ed. 2020. This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering.Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail.It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science.As an aid to self-study, it aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field.Each chapter has practical exercises to enable readers to check their progress. A full glossary of technical terms used is included.Principles of Data Mining includes descriptions of algorithms for classifying streaming data, both stationary data, where the underlying model is fixed, and data that is time-dependent, where the underlying model changes from time to time - a phenomenon known as concept drift. The expanded fourth edition gives a detailed description of a feed-forward neural network with backpropagation and shows how it can be used for classification.

Zustand: New. pp. 16.

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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

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Zustand: New. pp. 16.