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Mastering Predictive Analytics with R, Second Edition

You're reading from   Mastering Predictive Analytics with R, Second Edition Machine learning techniques for advanced models

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787121393
Length 448 pages
Edition 2nd Edition
Languages
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Authors (2):
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James D. Miller James D. Miller
Author Profile Icon James D. Miller
James D. Miller
Rui Miguel Forte Rui Miguel Forte
Author Profile Icon Rui Miguel Forte
Rui Miguel Forte
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Table of Contents (22) Chapters Close

Mastering Predictive Analytics with R Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Gearing Up for Predictive Modeling FREE CHAPTER 2. Tidying Data and Measuring Performance 3. Linear Regression 4. Generalized Linear Models 5. Neural Networks 6. Support Vector Machines 7. Tree-Based Methods 8. Dimensionality Reduction 9. Ensemble Methods 10. Probabilistic Graphical Models 11. Topic Modeling 12. Recommendation Systems 13. Scaling Up 14. Deep Learning Index

A little graph theory


Graph theory is a branch of mathematics that deals with mathematical objects known as graphs. Here, a graph does not have the everyday meaning that we are more used to talking about, in the sense of a diagram or plot with an x and y axis. In graph theory, a graph consists of two sets. The first is a set of vertices, which are also referred to as nodes. We typically use integers to label and enumerate the vertices. The second set consists of edges between these vertices.

Thus, a graph is nothing more than a description of some points and the connections between them. The connections can have a direction so that an edge goes from the source or tail vertex to the target or head vertex. In this case, we have a directed graph. Alternatively, the edges can have no direction, so that the graph is undirected.

A common way to describe a graph is via the adjacency matrix. If we have V vertices in the graph, an adjacency matrix is a V×V matrix whose entries are 0 if the vertex represented...

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