library(ISLR)
library(pls)
library(plotly)

# Base de datos Hitters. 
Hitters = Hitters
Hitters = na.omit(Hitters)

# Componentes principales de los predictores
x = model.matrix(Salary~., Hitters)[, -1]
y = Hitters$Salary
pc = prcomp(x, retx = TRUE, center = TRUE, scale. = TRUE)$x
pc = as.data.frame(pc)
pc$y = y
plot_ly(pc, x = ~PC1, y = ~PC2, z = ~PC3,
        marker = list(color = ~y, colorscale = c('#FFE1A1', '#683531'), showscale = TRUE)) %>% 
        add_markers()
plot(pc$PC1, log(y))

# Regresión de componenes principales
pcr.fit <- pcr(Salary ~ ., data = Hitters, scale = TRUE, validation = "CV")
summary(pcr.fit)
validationplot(pcr.fit, val.type = "MSEP")