Cancer mama
Enrique Pablos A00835037
2024-03-02
Ejercicio 2. Determinar cancer de
mama
1. Instalar paquetes y llamar
librerias
# install.packages("neuralnet")
library(neuralnet)
library(caret)## Loading required package: ggplot2## Warning: package 'ggplot2' was built under R version 4.3.1## Loading required package: lattice## Warning: package 'lattice' was built under R version 4.3.12. Obtener datos
cancer_df <- read.csv("/Users/kikepablos/Documents/Development/escuela/concentracion_ai/modulo_6/data_sources/cancer_de_mama.csv")
cancer_df$diagnosis <- ifelse(cancer_df$diagnosis == "M", 1, ifelse(cancer_df$diagnosis == "B", 0, NA))
index <-createDataPartition(cancer_df$diagnosis, p = 0.8, list = FALSE)
train_data <- cancer_df[index, ]
test_data <- cancer_df[-index, ]3. Generar red neuronal
set.seed(123)
rn2 <- neuralnet(diagnosis~., data=train_data)
plot(rn2, rep="best")
##
prediccion2 <- compute(rn2, test_data)
probabilidad2 <- prediccion2$net.result
resultado2 <- ifelse(probabilidad2>0.5,1,0)
resultado2## [,1]
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