How to make up the missing values in R language for cluster analysis
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
