I have several thousand documents that I want to put in to one or many categories (12 categories total) My current plan is to use Python and SciKit-learn to test multiple machine learning algorithms for which is most predictive.
I am to the point of creating a labeled training set by taking about a thousand of these documents and assigning labels to each. I have been unable to find a good explanation of how to best label these documents for multilabel classification. I am thinking of creating a csv with a column for the document's id number, and a column for each possible category. Then entering a 1 or 0 if it belongs in that category. Or I was thinking of coding each category as 1-12 and then just making one column where each category is listed but comma separated (1,3,6,12). Before I go through with this lengthy process I was looking for some feedback on how to best label text for multilabel classification.