Loadings and scores for the PCs
The primary goal of PCA is dimension reduction, which is often necessary to view high dimensional data. Plotting the PC scores in two dimensions is one way to visualize high dimensional data.
Diese Übung ist Teil des Kurses
Multivariate Probability Distributions in R
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
# Create data frame of scores
scores.state <- data.frame(___)
# Plot of scores labeled by state name
ggplot(data = scores.state, aes(x = ___, y = ___, label = ___) +
geom_text( alpha = 0.8, size = 3) +
ggtitle("PCA of states data")