Principal component analysis in r

library(FactoMineR)
library(factoextra)
res.pca = FactoMineR::PCA(X, scale.unit = TRUE, ncp = 5, graph = TRUE)
factoextra::fviz_eig(res.pca, addlabels = TRUE, ylim = c(0, 50))

Similar codes

1 vote338 views1 answer
R extract everything before character
R
0 vote348 views1 answer
How to build random forest in r
R
0 vote388 views1 answer
Rmarkdown put date
R
0 vote380 views2 answers
R code mutate
R
0 vote359 views1 answer
ISO 2 letter country code in r
R
0 vote454 views1 answer
Round multiple columns in r
R
0 vote391 views1 answer
Significance codes
R
0 vote370 views1 answer
R remove insignificant coefficient in output
R
0 vote375 views1 answer
Calculating RMSE, MAE, MSE, Rsquared manually in R
R
0 vote364 views1 answer
Decision tree r
R