Logistic regression predictions dont work I have this problem with logit, that when I want to create confusion matrix, it simply displays the real values in the first row and in the second row, there are never any numbers. I created a lot of models (individually for each country where I analyse occurence of an event 1-it happens, 0-it does not happen), but each logit has this problem.
I guess I am doing something wrong. So far, I checked for all the necessary assumptions, the only thing I didn't do, was k-fold cross validation and I did not divide model on training and testing set. Could that be a reason? Could someone explain why?

The inverse logit function produces continuous values strictly between 0 and 1, while a confusion matrix is based on predictions in $\{0, 1\}$.
So either you dichotomize the continuous predictions (which involves choosing a threshold), or you work with scoring measures like the logloss or AIC that can directly work with continuous predictions.
