DEMO

## Warning: package 'factoextra' was built under R version 4.1.1

## Loading required package: ggplot2

## Warning: package 'ggplot2' was built under R version 4.1.1

## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa

Triển khai mô hình PCA

Xuất dữ liệu về phương sai của các thành phần chính

##        eigenvalue variance.percent cumulative.variance.percent
## Dim.1    7.302028        14.042361                    14.04236
## Dim.2    4.150468         7.981669                    22.02403
## Dim.3    3.168974         6.094180                    28.11821
## Dim.4    2.627944         5.053739                    33.17195
## Dim.5    2.374756         4.566839                    37.73879
## Dim.6    2.168503         4.170198                    41.90899
## Dim.7    1.994919         3.836383                    45.74537
## Dim.8    1.973209         3.794632                    49.54000
## Dim.9    1.881935         3.619106                    53.15911
## Dim.10   1.750493         3.366333                    56.52544
##  [ reached 'max' / getOption("max.print") -- omitted 42 rows ]

screeplot

fviz_eig(pca, ylim = c(0,30), xlim = c(1,10))

Scoreplot

fviz_pca_ind(pca, label="all", habillage=dat2$Group)+xlim(-10, 10) + ylim (-7.5, 7.5)+labs(title= "PCA scoreplot",x="PC1 (14%)", y = "PC2 (8%)")

Loading plot

fviz_pca_var(pca, geom = c("point", "text"),col.var="contrib")+scale_color_gradient2(low="green", mid="red",high="blue", midpoint=2)+ theme_minimal()

Biplot

fviz_pca_biplot(pca, label="all",title = "PCA - Biplot",geom.var = c("arrow", "text"),geom.ind = c("point", "text"),habillage=dat2$Group)