glm.fit: algorithm did not converge error

user_13230827 0
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I have error below trying to use glm and can't fix it? How can I solve this problem?

setwd("C:/Users/ali.erkun/Desktop/524")
data<-read_excel("Take Home Dataset.xls")
attach(data)

L12M_LOAN_ACCEPT_2<-as.numeric(L12M_LOAN_ACCEPT)
#Zorlamadan dolayı ortaya çıkan NAs - we must omitt NAs
L12M_omitted<-na.omit(L12M_LOAN_ACCEPT_2)

summary(L12M_omitted)

data$L12M_LOAN_ACCEPT <-as.numeric(factor(ifelse(data$L12M_LOAN_ACCEPT == ".", 0,data$L12M_LOAN_ACCEPT)))

str(data)

fit <- glm(LABEL ~ ., family = binomial(link = "logit"), data = data, )

loanlogit_full <- glm(LABEL ~ ., family = binomial(link = "logit"), data = data) Warning messages: 1: glm.fit: algorithm did not converge 2: glm.fit: fitted probabilities numerically 0 or 1 occurred

glm statistics r
1 Answers

It's likely that you can achieve perfect separation of your response with one or more of your predictor variables. See this answer and the one that @John.G linked. If one of your independent variables perfectly predicts the outcome, the coefficient for that predictor will grow without bound (and therefore won't converge).

There are a number of ways to deal with this problem - https://stats.stackexchange.com/a/68917/275337 gives a very good overview of the options.

user_131575360
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