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 ejercicio forma parte del curso
Multivariate Probability Distributions in R
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# 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")