Looking for help-Building Models for Text Classification/TopicModeling/Clustering
I'm just getting familiarized with topic modeling/text classification using clustering or supervised learning to build models. Is there a way to edit or manually create part of a model so that I can force a category or ensure that key words that may not have been in the tagged data are included in future runs of the model?
I haven't posted my current process because I don't know where to start with the model building. The test data I am working with is a list of past exam questions. I want to run them through a process that categorizes them based on topic. Is there a way to adjust the model after running a training set of data to ensure that specific key words rank high in the distribution table?