Скачать с ютуб Principal Component Analysis in R Programming | How to Apply PCA | Step-by-Step Tutorial & Example в хорошем качестве

Principal Component Analysis in R Programming | How to Apply PCA | Step-by-Step Tutorial & Example

This video explains how to apply a Principal Component Analysis (PCA) in R. More details: https://statisticsglobe.com/principal... The video is presented by Cansu Kebabci, a data scientist and statistician at Statistics Globe. Find more information about Cansu here: https://statisticsglobe.com/cansu-keb... In the video, Cansu explains the steps and application of the Principal Component Analysis in R. Watch the video to learn more on this topic! Here can you find the first part of this series: Introduction to Principal Component Analysis (Pt. 1 - Theory):    • Introduction to Principal Component A...   Links to the tutorials mentioned in the video: Can PCA be Used for Categorical Variables? (Alternatives & Example): https://statisticsglobe.com/pca-categ... PCA Using Correlation & Covariance Matrix (Examples): https://statisticsglobe.com/pca-corre... Biplot of PCA in R (Examples): https://statisticsglobe.com/biplot-pca-r R code of this video: install.packages("MASS") install.packages("factoextra") install.packages("ggplot2") Load Libraries library(MASS) library(factoextra) library(ggplot2) Import biopsy data data(biopsy) dim(biopsy) Structure of Data str(biopsy) summary(biopsy) Delete Cases with Missingness biopsy_nomiss ＜- na.omit(biopsy) Exclude Categorical Data biopsy_sample ＜- biopsy_nomiss[,-c(1,11)] Run PCA biopsy_pca ＜- prcomp(biopsy_sample, scale = TRUE) Summary of Analysis summary(biopsy_pca) Elements of PCA object names(biopsy_pca) Std Dev of Components biopsy_pca$sdev Eigenvectors biopsy_pca$rotation Std Dev and Mean of Variables biopsy_pca$center biopsy_pca$scale Principal Component Scores biopsy_pca$x Scree Plot of Variance fviz_eig(biopsy_pca, addlabels = TRUE, ylim = c(0, 70)) Biplot with Default Settings fviz_pca_biplot(biopsy_pca) Biplot with Labeled Variables fviz_pca_biplot(biopsy_pca, label="var") Biplot with Colored Groups fviz_pca_biplot(biopsy_pca, label="var", habillage = biopsy_nomiss$class) Biplot with Customized Colored Groups and Variables fviz_pca_biplot(biopsy_pca, label="var", habillage = biopsy_nomiss$class, col.var = "black") + scale_color_manual(values=c("orange", "purple")) Follow me on Social Media: Facebook – Statistics Globe Page:   / statisticsglobecom   Facebook – R Programming Group for Discussions & Questions:   / statisticsglobe   Facebook – Python Programming Group for Discussions & Questions:   / statisticsglobepython   LinkedIn – Statistics Globe Page:   / statisticsglobe   LinkedIn – R Programming Group for Discussions & Questions:   / 12555223   LinkedIn – Python Programming Group for Discussions & Questions:   / 12673534   Twitter:   / joachimschork   Instagram:   / statisticsglobecom   TikTok:   / statisticsglobe