Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or cluste

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Yes, you can access Practical Graph Mining with R by Nagiza F. Samatova, William Hendrix, John Jenkins, Kanchana Padmanabhan, Arpan Chakraborty in PDF and/or ePUB format, as well as other popular books in Economics & Statistics for Business & Economics. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Chapman and Hall/CRC

Year

2013

ISBN

9781439860854

Edition

Topic

Economics

Subtopic

Statistics for Business & Economics

Index

Economics

Front Cover
Contents
List of Figures
List of Tables
Preface
1. Introduction
2. An Introduction to Graph Theory
3. An Introduction to R
4. An Introduction to Kernel Functions
5. Link Analysis
6. Graph-based Proximity Measures
7. Frequent Subgraph Mining
8. Cluster Analysis
9. Classification
10. Dimensionality Reduction
11. Graph-based Anomaly Detection
12. Performance Metrics for Graph Mining Tasks
13. Introduction to Parallel Graph Mining