Data mining with R learning with case studies
Data mining with R: learning with case studies

Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgments -- List of Figures -- List of Tables -- 1:Introduction -- 1.1 How to Read This Book -- 1.2 Reproducibility -- I R and Data Mining -- 2: Introduction to R -- 2.1 Starting with R -- 2.2 Basic Interac...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Torgo, Luís (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Boca Raton CRC Press, Taylor Francis Group [2017]
Ausgabe:Second edition
Schriftenreihe:Data mining and knowledge discovery series
Schlagworte:
R > Programm
Data Mining
Fallstudiensammlung
Online-Zugang:DE-92
DE-863
DE-862
DE-473
DE-19
Volltext
Zusammenfassung:Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgments -- List of Figures -- List of Tables -- 1:Introduction -- 1.1 How to Read This Book -- 1.2 Reproducibility -- I R and Data Mining -- 2: Introduction to R -- 2.1 Starting with R -- 2.2 Basic Interaction with the R Console -- 2.3 R Objects and Variables -- 2.4 R Functions -- 2.5 Vectors -- 2.6 Vectorization -- 2.7 Factors -- 2.8 Generating Sequences -- 2.9 Sub-Setting -- 2.10 Matrices and Arrays -- 2.11 Lists -- 2.12 Data Frames -- 2.13 Useful Extensions to Data Frames
2.14 Objects, Classes, and Methods -- 2.15 Managing Your Sessions -- 3: Introduction to Data Mining -- 3.1 A Bird's Eye View on Data Mining -- 3.2 Data Collection and Business Understanding -- 3.2.1 Data and Datasets -- 3.2.2 Importing Data into R -- 3.2.2.1 Text Files -- 3.2.2.2 Databases -- 3.2.2.3 Spreadsheets -- 3.2.2.4 Other Formats -- 3.3 Data Pre-Processing -- 3.3.1 Data Cleaning -- 3.3.1.1 Tidy Data -- 3.3.1.2 Handling Dates -- 3.3.1.3 String Processing -- 3.3.1.4 Dealing with Unknown Values -- 3.3.2 Transforming Variables -- 3.3.2.1 Handling Different Scales of Variables
3.3.2.2 Discretizing Variables -- 3.3.3 Creating Variables -- 3.3.3.1 Handling Case Dependencies -- 3.3.3.2 Handling Text Datasets -- 3.3.4 Dimensionality Reduction -- 3.3.4.1 Sampling Rows -- 3.3.4.2 Variable Selection -- 3.4 Modeling -- 3.4.1 Exploratory Data Analysis -- 3.4.1.1 Data Summarization -- 3.4.1.2 Data Visualization -- 3.4.2 Dependency Modeling using Association Rules -- 3.4.3 Clustering -- 3.4.3.1 Measures of Dissimilarity -- 3.4.3.2 Clustering Methods -- 3.4.4 Anomaly Detection -- 3.4.4.1 Univariate Outlier Detection Methods -- 3.4.4.2 Multi-Variate Outlier Detection Methods
Beschreibung:1 Online-Ressource (xix, 405 Seiten) Illustrationen, Diagramme
ISBN:9781315399102
9781315399096
DOI:10.1201/9781315399102
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