Created
May 10, 2021 19:27
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| --- | |
| title: "IC de precisão, recall, F1..." | |
| output: html_notebook | |
| --- | |
| ```{r setup, include=FALSE, message=FALSE, warning=FALSE} | |
| knitr::opts_chunk$set(echo = TRUE) | |
| library(tidyverse) | |
| library(hrbrthemes) | |
| theme_set(theme_ipsum_rc()) | |
| library(boot) | |
| library(broom) | |
| ``` | |
| ```{r} | |
| conj_teste = tibble( | |
| imagem = 1:200, | |
| label = c(rep("Com gato", 100), rep("Sem gato", 100)) | |
| ) | |
| ``` | |
| ```{r} | |
| resultado_amostra = bind_rows( | |
| conj_teste %>% | |
| mutate( | |
| classificador = "Modelo 1", | |
| previsao = if_else( | |
| runif(200) > .2, | |
| label, | |
| if_else(label == "Com gato", "Sem gato", "Com gato")) | |
| ), | |
| conj_teste %>% | |
| mutate( | |
| classificador = "Modelo 2", | |
| previsao = if_else( | |
| runif(200) > .5, | |
| "Com gato", | |
| "Sem gato" | |
| ) | |
| ) | |
| ) | |
| ``` | |
| ```{r} | |
| resultado_amostra %>% | |
| group_by(classificador) %>% | |
| summarise( | |
| n = n(), | |
| vp = sum(label == "Com gato" & label == previsao), | |
| fp = sum(label == "Com gato" & label != previsao), | |
| vn = sum(label == "Sem gato" & label == previsao), | |
| fn = sum(label == "Sem gato" & label == previsao), | |
| ) | |
| ``` | |
| ```{r} | |
| precisao = function(d, i){ | |
| d %>% | |
| slice(i) %>% | |
| summarise( | |
| vp = sum(label == "Com gato" & label == previsao), | |
| fp = sum(label == "Com gato" & label != previsao), | |
| precisao = vp / (vp + fp) | |
| ) %>% | |
| pull(precisao) | |
| } | |
| ``` | |
| ```{r} | |
| resultado_amostra %>% | |
| filter(classificador == "Modelo 1") %>% | |
| precisao(i = 1:nrow(.)) | |
| ``` | |
| ```{r} | |
| booted <- boot(data = resultado_amostra %>% filter(classificador == "Modelo 1"), | |
| statistic = precisao, | |
| R = 2000) | |
| estimado_m1 = tidy(booted, | |
| conf.level = .95, | |
| conf.method = "bca", | |
| conf.int = TRUE) | |
| glimpse(estimado_m1) | |
| ``` | |
| ```{r} | |
| booted <- boot(data = resultado_amostra %>% filter(classificador == "Modelo 2"), | |
| statistic = precisao, | |
| R = 2000) | |
| estimado_m2 = tidy(booted, | |
| conf.level = .95, | |
| conf.method = "bca", | |
| conf.int = TRUE) | |
| glimpse(estimado_m2) | |
| ``` | |
| ```{r} | |
| bind_rows(modelo1 = estimado_m1, | |
| modelo2 = estimado_m2, | |
| .id = "modelo") %>% | |
| ggplot(aes( | |
| ymin = conf.low, | |
| y = statistic, | |
| ymax = conf.high, | |
| x = modelo | |
| )) + | |
| geom_linerange() + | |
| geom_point(color = "steelblue", size = 3) + | |
| geom_text( | |
| aes( | |
| y = conf.high, | |
| label = str_glue("[{round(conf.low, 2)}, {round(conf.high, 2)}]") | |
| ), | |
| size = 3, | |
| nudge_x = -.05, | |
| show.legend = F | |
| ) + | |
| scale_y_continuous(limits = c(0, 1)) + | |
| labs( | |
| title = "Precisão dos classificadores", | |
| x = "", y = "Precisão") + | |
| coord_flip() | |
| ``` | |
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