I have created a logistic regression model using the built in iris dataset in R...
# Includes iris dataset.
library(datasets)
# Dummy variable to predict.
iris$dummy.virginica.iris <- 0
iris$dummy.virginica.iris[iris$Species == 'virginica'] <- 1
iris$dummy.virginica.iris
# Logistic regression model.
glmfit<-glm(dummy.virginica.iris ~ Petal.Width,
data = iris,
family = 'binomial')
summary(glmfit)
How would I create a classifier based on this model with a suitable cut-off value such as 0.5? Any suggestions or help would be greatly appreciated.