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.
Este exercício faz parte do curso
Multivariate Probability Distributions in R
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
# 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")