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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

Correcting for missing values

Although it is always important to understand the source of your missing values, how you ultimately handle them depends upon the technique that you use to analyse your data sets. For example, classification methods such as decision trees and random forests know how to deal with missing values, since they can treat them as a separate class, and you can safely leave them in the model. However, if a variable has a large amount of missing values, say > 20%, you might want to look at imputation techniques, or try to find a better variable that measures the same thing.

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Publisher Resources

ISBN: 9781785886188Supplemental Content