Is the only reason why fitted probabilities of 0 or 1 occur is that some of your predicting variables(x) are perfect linear combinations of the target(y) variable? Is there any other reason?
closed as unclear what you're asking by Michael Chernick, AdamO, kjetil b halvorsen, Stephan Kolassa, mdewey Jan 23 '18 at 12:10
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For the reasons, in addition to the situation that the predictor x is a perfect linear combination of the response y, quasi-complete separation will also induce the same error.
Theoretically, this occurs when the maximum likelihood estimate of your regression coefficient does not exist. Simply put, for example, imagine we have an 2*2 contingency table formed by the "problematic" predictor x and the response y, it is possible that there is an 0 in the table, which obstructs the calculation of MLE. This situation (quasi-complete separation) induce the "fitted probabilities numerically 0 or 1 occurred" error. Hope it helps.