Lot of errors by using the auto model to compare the prediction models
Hello everybody,
I am a freshman in Data mining and I don't know which model I should use for my classification task. So I want to use the Auto Model to check which model works best for my data. But no model works, all show errors with these mistakes:
Cannot execute log reg calibration learning: Error while training the H2O model: Illegal argument(s) for GLM model: ERRR on field: _response: Response cannot be constant. ERRR on field: _train: Training data must have at least 2 features (incl. response).
I am a freshman in Data mining and I don't know which model I should use for my classification task. So I want to use the Auto Model to check which model works best for my data. But no model works, all show errors with these mistakes:
Cannot execute log reg calibration learning: Error while training the H2O model: Illegal argument(s) for GLM model: ERRR on field: _response: Response cannot be constant. ERRR on field: _train: Training data must have at least 2 features (incl. response).
Does anyone know what I can do?
In another forum I saw one of these errors and I think it could be a problem, that I have too many outcome variables. I have a data set with approximatly 850 rows and 40 outcome variables. Could this be the problem?
Thank you very much.
Kind regards