I want to classify a dataset of support tickets which mostly contain text in the description field and sometimes server logs in a separate field.
The log field is not always there but when it's present, it's a good indicator of the target class of the ticket.
I have created a CNN based classifier which can classify the tickets based on the log field, and a SVM clf with TFIDF based features for the description field.
I am thinking of adding the output probabilities of the CNN classifier in TFIDF based SVM classifier to combine the models as a feature column.
Is there a better way to combine these models?
Is there a better way to approach this problem, without having two separate models?