compare_gam.R

data(kyphosis, package = "gam")
y <- ifelse(kyphosis$Kyphosis == "present", 1, 0)
x <- scale(kyphosis[, -1])
### FIT A GRNN
net1 <- grnn.fit(x = x, y = y)
test <- grnn.search_auc(net1, sigmas = gen_sobol(min = 0.5, max = 1.5, n = 50), nfolds = 20)
net2 <- grnn.fit(x = x, y = y, sigma = min(test$best$sigma))
### FIT A GAM
library(gam)
gam1 <- gam(y~ Age + Number + Start, data = data.frame(y, x), family = binomial)
step <- step.Gam(gam1, data = data.frame(x, y), direction = "both", 
                 scope = list("Age"    = ~1 + Age + s(Age, 3) + s(Age, 4) + s(Age, 5), 
                              "Number" = ~1 + Number + s(Number, 3) + s(Number, 4) + s(Number, 5), 
                              "Start"  = ~1 + Start + s(Start, 3)+ s(Start, 4) + s(Start, 5)))
# Start:  y ~ Age + Number + Start; AIC= 69.3799
# Step:1 y ~ s(Age, 3) + Number + Start ; AIC= 66.1469
# Step:2 y ~ s(Age, 3) + Number + s(Start, 3) ; AIC= 64.1875
gam2 <- gam::gam(y ~ s(Age, 3) + Number + s(Start, 3), data = data.frame(x, y), family = binomial)
### PLOTTING
par(mfrow = c(2, 3))
for (i in 1:ncol(net2$x)) grnn.margin(net2, i)
plot(gam2, col = "blue", lwd = 5)