This is a common issue caused by some parameters in the model becoming theoretically infinite. It can happen when the model perfectly predicts the response, or if there are more parameters in the model than can be estimated by the data (that is, with sparse data, where "sparse" means that there are few or no repeats of each setting of the covariates). One solution is to reduce the number of variables and/or change continuous variables to categorical. There is no way to know which variable to eliminate or categorize because all are involved simultaneously. The resulting model is usually good at classifying observations, but inferences about the parameters should be avoided.
[Previously JMP Note 36686]