This should do the trick:
history2 <- as.data.frame(lapply(history, as.factor))
Mind you that read.csv() by default reads string vectors as factors, so
that declaring the variables as factors should only be necessary for the
numeric ones, like income. Using as.factor() in factor variables may
dro
Hi guys,
I am running glm(y~., data = history,family=binomial)-essentially, logistic
regression for credit scoring (y = 0 or 1). The dataset 'history' has 14
variables, a few examples:
history <- read.csv("history.csv". header = TRUE)
1> 'income = 100,200,300 (these are numbers in my dataset; howe
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