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Applied Supervised Learning with R

You're reading from  Applied Supervised Learning with R

Product type Book
Published in May 2019
Publisher
ISBN-13 9781838556334
Pages 502 pages
Edition 1st Edition
Languages
Authors (2):
Karthik Ramasubramanian Karthik Ramasubramanian
Profile icon Karthik Ramasubramanian
Jojo Moolayil Jojo Moolayil
Profile icon Jojo Moolayil
View More author details
Toc

Table of Contents (12) Chapters close

Applied Supervised Learning with R
Preface
1. R for Advanced Analytics 2. Exploratory Analysis of Data 3. Introduction to Supervised Learning 4. Regression 5. Classification 6. Feature Selection and Dimensionality Reduction 7. Model Improvements 8. Model Deployment 9. Capstone Project - Based on Research Papers Appendix

NCCTG Lung Cancer Data


NCCTG Lung Cancer Data from survival in patients with advanced lung cancer is from the North Central Cancer Treatment Group. The data is a collection of few metadata, such as which institution collected it, age of the patient, sex, and so on. The performance scores in this dataset rates how well the patient can perform the daily activities. The most important variable in any survival analysis dataset is the knowledge about the time-to-event, for example, time until death.

Survival analysis is usually defined as a set of methods for examining data where the outcome variable is the time till the incidence of an event of interest.

Figure 4.21: Variables and its descriptions of North Central Cancer Treatment Group

In the next exercise, we will learn how to create the survival object using the method Surv from the survival package. Note that in the summary of the dataset after adding the survival object, two additional variables SurvObject.time and SurvObject.status are created...

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