Created
September 2, 2021 07:29
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RでROC曲線 (precrecパッケージ)
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library(tidyverse) | |
# 適当なロジスティック回帰モデルを作る | |
b <- 10 | |
a <- 3 | |
x <- rnorm(100, mean = 10, sd = 5) | |
e <- rnorm(100, sd = 12) | |
y <- (a * x) + b + e | |
y <- if_else(y >= mean(y), 1, 0) | |
logi_res <- glm(y ~ x, family = binomial(link = "logit")) | |
# precrecパッケージの読み込み | |
library(precrec) | |
# 実測値と予測値をmmdata形式?でまとめる | |
# 実際には、検証用データでやったほうが良いに決まっている | |
logi_mmdata <- mmdata(fitted(logi_res), y) | |
# ROC曲線などの指標を算出する | |
# mode = "basic" オプションを指定すると正解率、適合率などが得られる | |
logi_curve <- evalmod(logi_mmdata) | |
# ggplot2でROC曲線を描画する | |
# library(ggplot2) | |
autoplot(logi_curve, "ROC") + theme_classic(base_family = "Source Han Code JP", base_size = 18) + theme(legend.position = "none") |
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