Cours métaméthodes

05_Metamethods/.~lock.cours.odp#

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+,maxx,satamaxx-laptop,02.05.2018 00:03,file:///home/maxx/.config/libreoffice/4;

05_Metamethods/figures.R

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+library(tidyverse)
+library(shiny)
+library(miniUI)
+library(broom)
+
+tibble(x = runif(20, 0, 10),
+       y = x^2 - 2*x + rnorm(20, 0, 5)) -> df
+
+df %>%
+  ggplot() +
+  aes(x = x, y = y) +
+  geom_point() -> g
+
+df %>%
+  sample_n(10) -> train
+
+df %>%
+  anti_join(train) -> test
+
+train %>%
+  ggplot() +
+  aes(x = x, y = y) +
+  geom_point() -> gtrain
+
+gtrain +
+  geom_point(data = test, aes(color = "red")) +
+  theme(legend.position = "none") -> g
+
+ggsave(filename = "set.png", plot = g)
+
+powers <- function(df, n)
+{
+  for (i in 1:n)
+    df[[str_c("x", i)]] <- df$x^i
+
+  df
+}
+
+LM <- function(df, n)
+{
+  str_c("y ~ ", str_c("x", 1:n, collapse = " + ")) %>% as.formula -> form
+
+  df <- powers(df, n)
+
+  lm(form, data = df)
+}
+
+PREDICT <- function(train, test, n)
+{
+  model <- LM(train, n)
+
+  test <- powers(test, n)
+
+  mean((test$y - predict(model, test))^2)
+}
+
+Fggfun <- function(model)
+{
+  model %>%
+    pull(estimate) -> est
+  Vectorize(
+            function(x)
+            {
+              sum(x^(0:(length(est) - 1)) * est)
+            })
+}
+
+1:9 %>% map(~LM(train, .) %>% tidy %>% Fggfun) -> ggfuns
+
+1:9 %>%
+  map(function(n)
+      {
+        LM(train, n) %>%
+          tidy %>%
+          Fggfun %>%
+          stat_function(fun = .)
+      }) -> regs
+
+1:9 %>%
+  map(function(n)
+      {
+        (gtrain + regs[n]) %>%
+          ggsave(filename = str_c("train_", n, ".png"))
+      })
+
+1:9 %>%
+  map(function(n)
+      {
+        (g + regs[n]) %>%
+          ggsave(filename = str_c("all_", n, ".png"))
+      })
+
+(
+1:9 %>%
+  map_dbl(~LM(train, .) %>% glance %>% pull(r.squared)) %>%
+  tibble(x = 1:9, y = .) %>%
+  ggplot() +
+  aes(x = x, y = y) +
+  geom_point() +
+  geom_line() +
+  scale_x_continuous(breaks = 0:10)
+) %>%
+ggsave(filename = "rsquared.png", plot = .)
+
+(
+1:9 %>%
+  map_dbl(~PREDICT(train, test, .)) %>%
+  tibble(x = 1:9, y = .) %>%
+  ggplot() +
+  aes(x = x, y = y) +
+  geom_point() +
+  geom_line() +
+  scale_x_continuous(breaks = 0:10)
+) %>%
+ggsave(filename = "error.png", plot = .)