In skpalominos/DSutilsR: Funciones utiles para analisis estadísticos

knitr::opts_chunk$set(echo = TRUE)

library(ggplot2)
library(plotly)
library(dplyr)
library(gridExtra)
library(DSutilsR)
library(yardstick)
theme_set(theme_grey())

Información adicional

M

Metricas de Performance

res <- eval_binary_performance(Y,pred)

Valores Generales

M <- matrix(ncol=3,nrow=2)
M[1,] <- round(c(res$auc,res$ks,res$tpr),3)
M[2,] <- c(1,1,1) 
colnames(M) <- c("AUC","KS","tpr")
t(M[1,c(1,2,3)]) %>% kable(escape = F, align = "c") %>%
  kable_styling(c("striped", "condensed"), full_width = F)

Grafica Curva de ROC

InformationValue::plotROC(Y,pred)

Gráfica Curva de Lift Acumulada

plot(res$plot_lift)

Grafica KS

plot(res$plot_ks)

Matriz de confusion por threshold

# grafico matriz de consusion

plot_confusion_matrix <- function(Y,pred,tresh){
  df <- data.frame(Y,pred) %>% mutate(Y=if_else(Y==1,"Yes","No") %>% as.factor(),
                                      pred=if_else(pred>tresh,"Yes","No") %>% as.factor())
  cm <- conf_mat(df,Y,pred)
  autoplot(cm, type = "heatmap")+scale_fill_gradient(low="#D6EAF8",high = "#2E86C1")+ggtitle(paste0("Confusion Matrix treshold: ",tresh))
}

# graficos por treshold

L <- seq(0.1,0.9,0.1) %>% purrr::map(~plot_confusion_matrix(df_test$chd,df_test$prob,.x))
L

skpalominos/DSutilsR documentation built on Nov. 14, 2021, 11:15 p.m.