🦉 🎤   RapidMiner Wisdom 2020 - CALL FOR SPEAKERS   🦉 🎤
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Whether it's a cool RapidMiner trick or a use case implementation, we want to see what you have.
Form link is below and deadline for submissions is November 15. See you in Boston!
Model Apllier problem
I created a model, learned on a training set with several nominal attributes (e.g. MONTH, OVERALL_STATE), everything seemed fine until I applied my model on a test set (containing only one example). I have following warnings in a log:
[Warning] KernelDistribution: The number of nominal values is not the same for training and application for attribute 'MONTH', training: 12, application: 1
[Warning] KernelDistribution: The number of nominal values is not the same for training and application for attribute 'OVERALL_STATE', training: 12, application: 1
When I put another 11 examples with range of my month nominal attribute, warning for month disappears. But I want to classify just one example, how should I do that without warnings? When I output values of DataRow for each attribute (model creation and application is done from Java code), all nominal attributes have value 0 (instead of values given in test set), what I am doing wrong? Thank you for your help.