learning_plots_lrml.R

p1 <- df %>% 
  ggplot(aes(x=x, y=y)) + 
  geom_abline(aes(intercept = b0, 
                  slope = b1, 
                  colour = -sse, 
                  frame = model_iter), 
              data = model_i, 
              alpha = .50 
              ) +
  geom_point(alpha = 0.4) + 
  geom_abline(aes(intercept = b0, 
                  slope = b1), 
              data = model_i[100, ], 
              alpha = 0.5, 
              size = 2, 
              colour = "dodger blue") +
  geom_abline(aes(intercept = b0, 
                  slope = b1),
              data = model_i[1, ],
              colour = "red", 
              alpha = 0.5,
              size = 2) + 
  scale_color_continuous(low = "red", high = "grey") +
  guides(colour = FALSE) +
  theme_minimal()

p2 <- model_i[1:30,] %>%
  ggplot(aes(model_iter, sse, colour = -sse)) + 
  geom_point(alpha = 0.4) +
  theme_minimal() +
  labs(x = "Model iteration", 
       y = "Sum of Sqaured errors") + 
  scale_color_continuous(low = "red", high = "dodger blue") +
  guides(colour = FALSE)