I have a dataset of text-documents, which are all considered valid. Also I have a set of manually defined features that are required to be in the document for it to be considered valid. The features can be represented by different words(synonyms).
I want to test new documents in how much they adhere to the features. It is not a binary classification problem, as I don't have examples of invalid documents. Furthermore, the documents that are not valid will most likely be incomplete, so they will lack some. The result should be continuous and point to the feature that are missing. What should I use?