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Machine Learning with R Cookbook, Second Edition

You're reading from   Machine Learning with R Cookbook, Second Edition Analyze data and build predictive models

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781787284395
Length 572 pages
Edition 2nd Edition
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Authors (2):
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Ashish Bhatia Ashish Bhatia
Author Profile Icon Ashish Bhatia
Ashish Bhatia
Yu-Wei, Chiu (David Chiu) Yu-Wei, Chiu (David Chiu)
Author Profile Icon Yu-Wei, Chiu (David Chiu)
Yu-Wei, Chiu (David Chiu)
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Table of Contents (15) Chapters Close

Preface 1. Practical Machine Learning with R FREE CHAPTER 2. Data Exploration with Air Quality Datasets 3. Analyzing Time Series Data 4. R and Statistics 5. Understanding Regression Analysis 6. Survival Analysis 7. Classification 1 - Tree, Lazy, and Probabilistic 8. Classification 2 - Neural Network and SVM 9. Model Evaluation 10. Ensemble Learning 11. Clustering 12. Association Analysis and Sequence Mining 13. Dimension Reduction 14. Big Data Analysis (R and Hadoop)

Extracting silhouette information from clustering

Silhouette information is a measurement to validate a cluster of data. In the previous recipe, we mentioned that the measurement of a cluster involves the calculation of how closely the data is clustered within each cluster, and measures how far different clusters are apart from each other. The silhouette coefficient combines the measurement of the intracluster and intercluster distance. The output value typically ranges from 0 to 1; the closer to 1, the better the cluster is. In this recipe, we will introduce how to compute silhouette information.

Getting ready

In order to extract the silhouette information from a cluster, you need to have the previous recipe completed by...

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