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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
Languages
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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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Toc

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)

Viewing the summary of survival analysis

Once we have the survfit object, we can see the summary of it to get some insights.

Getting ready

You need to have completed the previous recipe and have the sfit object from cancer dataset.

How to do it...

Perform the following steps to view the summary:

> sfit <- survfit(Surv(time, status)~sex, data=cancer)
> sfit
Output
Call: survfit(formula = Surv(time, status) ~ sex, data = cancer)

n events median 0.95LCL 0.95UCL
sex=1 138 112 270 212 310
sex=2 90 53 426 348 550


> summary(sfit)
The following are a few lines from the output...
lock icon The rest of the chapter is locked
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