Samatova / Hendrix / Jenkins Practical Graph Mining with R

1. Auflage 2013
ISBN: 978-1-4398-6085-4
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 495 Seiten

Reihe: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

Integrating two important aspects of computer science (graph-based modeling and data mining techniques), this book provides a practical, do-it-yourself approach for extracting interesting patterns from graph data. The self-contained text requires no prerequisite knowledge of data mining and includes many worked examples, exercises with solutions, and real-world applications and data sets. Each algorithm is presented with accompanying R code. A supporting website features additional resources, including PowerPoint slides, R code, and data sets.

Autoren/Hrsg.

Samatova, Nagiza F.

Hendrix, William

Jenkins, John

Padmanabhan, Kanchana

Chakraborty, Arpan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

Introduction. Link Analysis. Graph-Based Proximity Measures. Cluster Analysis. Classification. Frequent Subgraph Mining. Graph-Based Anomaly Detection. Dimensionality Reduction. Introduction to Parallel Graph Mining.