Skip to Content
Practical Predictive Analytics
book

Practical Predictive Analytics

by Ralph Winters
June 2017
Beginner to intermediate content levelBeginner to intermediate
576 pages
15h 22m
English
Packt Publishing
Content preview from Practical Predictive Analytics

Transforming service calls to a binary variable

Variables with a higher number of levels will often be difficult to manage even though there may be statistically significant differences shown in the curves. This can be due to the smaller sizes of the groups. Rather than try to analyse all the groups at once, it often makes more sense to first find a cutoff point that collapses the variable into a binary outcome.

For example, running the survdiff() function on the number of service calls (ranging from 0 to 5) shows a significant difference between the individual survival curves:

> survdiff(SurvObj ~ Xservice.calls, data = ChurnStudy)Call:survdiff(formula = SurvObj ~ Xservice.calls, data = ChurnStudy)                    N Observed Expected (O-E)^2/E (OE)^2/V ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Data Superstream: Analytics Engineering

Data Superstream: Analytics Engineering

Alistair Croll, Anna Filippova, Emilie Schario, Lewis Davies, Jacob Frackson, Benn Stancil, Nick Acosta, Elizabeth Caley
R: Predictive Analysis

R: Predictive Analysis

Tony Fischetti, Eric Mayor, Rui Miguel Forte
Python: Advanced Predictive Analytics

Python: Advanced Predictive Analytics

Ashish Kumar, Joseph Babcock

Publisher Resources

ISBN: 9781785886188Supplemental Content