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ANNs don't work like that. If a certain item is not in your training set, and you pass that item as an input to your network then it will classify that item to the closest possible set (ideally).
One possible solution is using a regression model, that way you can possibly use the classification error to penalise this misclassification. But this method is pretty dangerous, and not recommended.
