Modelos

library(tidyverse)

package 㤼㸱tidyverse㤼㸲 was built under R version 3.6.3Registered S3 methods overwritten by 'dbplyr':
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package 㤼㸱ggplot2㤼㸲 was built under R version 3.6.3package 㤼㸱tibble㤼㸲 was built under R version 3.6.3package 㤼㸱tidyr㤼㸲 was built under R version 3.6.3package 㤼㸱readr㤼㸲 was built under R version 3.6.3package 㤼㸱purrr㤼㸲 was built under R version 3.6.3package 㤼㸱dplyr㤼㸲 was built under R version 3.6.3package 㤼㸱stringr㤼㸲 was built under R version 3.6.3package 㤼㸱forcats㤼㸲 was built under R version 3.6.3-- Conflicts ------------------------------------------ tidyverse_conflicts() --
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library(ISLR)

package 㤼㸱ISLR㤼㸲 was built under R version 3.6.3

datos <- Don_matias_1


head(datos)

default <- Don_matias_1$Xanthomonas
balance<- Don_matias_1$Northing + Don_matias_1$Easting

modelo_logistico <- glm(default ~ balance, data = datos, family = "binomial")

ggplot(data = datos, aes(x = balance, y = default)) +
  geom_point(aes(color = as.factor(default)), shape = 1) + 
  stat_function(fun = function(x){predict(modelo_logistico,
                                          newdata = data.frame(balance = x),
                                          type = "response")}) +
  theme_bw() +
  labs(title = "Regresión logística Don matias 2",
       y = "Probabilidad default") +
  theme(legend.position = "none")

datos1 <- don_matias_3


head(datos1)

default1 <- don_matias_3$Xanthomonas
balance1<- don_matias_3$Northing + don_matias_3$Easting

modelo_logistico1 <- glm(default1 ~ balance1, data = datos1, family = "binomial")

ggplot(data = datos1, aes(x = balance1, y = default1)) +
  geom_point(aes(color = as.factor(default1)), shape = 1) + 
  stat_function(fun = function(x){predict(modelo_logistico1,
                                          newdata = data.frame(balance1 = x),
                                          type = "response")}) +
  theme_bw() +
  labs(title = "Regresión logística Don matias 1",
       y = "Probabilidad default") +
  theme(legend.position = "none")

datos2 <- don_matias_2


head(datos2)

default2 <- don_matias_2$Xanthomonas
balance2<- don_matias_2$Northing + don_matias_2$Easting

modelo_logistico2 <- glm(default2 ~ balance2, data = datos2, family = "binomial")

ggplot(data = datos2, aes(x = balance2, y = default2)) +
  geom_point(aes(color = as.factor(default2)), shape = 1) + 
  stat_function(fun = function(x){predict(modelo_logistico2,
                                          newdata = data.frame(balance2 = x),
                                          type = "response")}) +
  theme_bw() +
  labs(title = "Regresión logística Don matias 3",
       y = "Probabilidad default") +
  theme(legend.position = "none")