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Introduction to data mining /

By: Tan, Pang-Ning [author.].
Contributor(s): Steinbach, Michael [author.] | Karpatne, Anuj [author.] | Kumar, Vipin, 1956- [author.].
Publisher: Harlow : Pearson Education, [2020]Edition: Second edition, global edition.Description: 859 pages : illustrations ; 24 cm.Content type: text | text Media type: unmediated Carrier type: volumeISBN: 9780273769224.Subject(s): Data mining | Artificial intelligence | Machine learningDDC classification: 006.312
Contents:
Introduction - Data - Classification: Basic Concepts and Techniques - Association Analysis: Basic Concepts and Algorithms - Cluster Analysis: Basic Concepts and Algorithms - Classification: Alternative Techniques - Association Analysis: Advanced Concepts - Cluster Analysis: Additional Issues and Algorithms - Anomaly Detection - Avoiding False Discoveries - Author Index - Subject Index - Copyright Permissions.
Summary: Introduction to Data Mining, Second Edition, is intended for use in the Data Mining course. Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.
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Item type Current library Call number Status Date due Barcode Item holds
Standard Loan Standard Loan ATU Sligo Yeats Library Main Lending Collection 006.312 TAN (Browse shelf(Opens below)) Available 0084571
Standard Loan Standard Loan ATU Sligo Yeats Library Main Lending Collection 006.312 TAN (Browse shelf(Opens below)) Available 0084570
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Includes bibliographical references and indexes.

Introduction - Data - Classification: Basic Concepts and Techniques - Association Analysis: Basic Concepts and Algorithms - Cluster Analysis: Basic Concepts and Algorithms - Classification: Alternative Techniques - Association Analysis: Advanced Concepts - Cluster Analysis: Additional Issues and Algorithms - Anomaly Detection - Avoiding False Discoveries - Author Index - Subject Index - Copyright Permissions.

Introduction to Data Mining, Second Edition, is intended for use in the Data Mining course. Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

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