supervised_learning.py handles input directories

By default writes out an individual results directory for each table contained within the input directory. If the tables are rarefied at the same depth (via multiple_rarefactions_even_depth.py), then the user has the option to "collate" the results into a single results file, similar to otu_category_significance.py

To avoid confusion, the -o output fp is now a required parameter