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I built a logistics regression model for iris dataset for versicolor and virginica species using the following code, however I got the following error.

Warning messages: 1: glm.fit: algorithm did not converge 2: glm.fit: fitted probabilities numerically 0 or 1 occurred

what am in doing wrong ?

library(ggplot2)
library(datasets)
library(caTools)

cat("\f")

ir_data <- iris

str(ir_data)
head(ir_data)

sum(is.na(ir_data))

set.seed(100)

# Fitting a logistic regression model to the iris data set
iris_small <- 
  iris %>%
  filter(Species %in% c("virginica", "versicolor"))

samp = sample.split(iris_small$Species, SplitRatio=0.75)

train = iris_small[samp,]
test  = iris_small[!samp,]

# Model
glm_out1 <- glm(Species ~ Sepal.Length + Sepal.Width + Petal.Width + Petal.Length, data=train, family=binomial)
summary(glm_out1)
npkp
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  • https://stackoverflow.com/questions/8596160/why-am-i-getting-algorithm-did-not-converge-and-fitted-prob-numerically-0-or https://stackoverflow.com/questions/61047697/glm-fit-algorithm-did-not-converge-error – dcsuka Oct 15 '22 at 17:17

0 Answers0