updated pascal style results
respecting existing split for ava_style to see if gets better performance
write_data_in_vw_format function, helper, and test
tests for vw caching
tests for forming binary and regression dataset dicts in predict.py
additional test for get_binary_or_regression_dataset
successfully training with cross validation
messed around with using tee to split feat file reading into filters;
ended up just doing it in parallel
simple binary data tests: confirm that features give different results
updated simple dataset test: now unbalanced classes
lots of work on how VW and predict work resulting in small updates, and
new ava_style results
get_multiclass_dataset working (not multi label yet)
plotting feature comparisons in multi class metrics, including to AVA
finished multi class multi label (test only) predict dataset function
OAA mode for VW implemented, with tests
now loading multi class prediction results for metrics
using proper voc2012 split info (less images, using val as test)
predict multi class experiments and additional cmdline params