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This article mainly explains "how R language completes missing values for cluster analysis". The content of the explanation is simple and clear, and it is easy to learn and understand. let's study and learn "how R language completes missing values for cluster analysis".

In an ideal state, we want the data to have no missing values. Unfortunately, missing values occur from time to time for a variety of reasons. This will cause problems. Cluster analysis can not be carried out on the incomplete data matrix.

Husson and Josse wrote a package called missMDA, which can be populated with missing values with the imputePCA () function.

Library ("missMDA") df=read.table ("aa.txt", header = T _ names = 1 _ df=log1p (df) res.comp

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