Decision boundary for MLP

nnet-decision-boundary.R

set.seed(1)
pts <- seq(0, 360, 10)

x1 <- c(sapply(pts, function(x) cos(x)), 
        sapply(pts, function(x) cos(x) * 4), 
        sapply(pts, function(x) cos(x) * 6))

x2 <- c(sapply(pts, function(x) sin(x)), 
        sapply(pts, function(x) sin(x) * 4),
        sapply(pts, function(x) sin(x) * 6))

data <- data.frame(x1, x2)

data$y <- as.factor(c(rep(0, length(pts)), rep(1, length(pts)), rep(2, length(pts))))

fit <- nnet(y ~ ., data, size = 40)

library(ggplot2)
py <- seq(-10, 10, 0.1)
px <- seq(-10, 10, 0.1)
grid <- expand.grid(px, py)
colnames(grid) <- c('x1', 'x2')
grid$pred <- as.numeric(predict(fit, grid, type = 'class'))

colnames(grid) <- c('x', 'y', 'z')
  
ggplot() + 
  stat_contour(data = grid, aes(x = x, y = y, z = z), alpha = 0.9) +
  geom_point(data = data, aes(x = x1, y = x2, color = y)) +
  coord_fixed() + 
  theme_bw() +
  xlab('x1') + 
  ylab('x2')