Added more functions and other minot cleanup
Added more functions and other minot cleanup

1. train_viewed_data_uid_cid - Convert user / coupon hash info to user / coupon IDs

2. random_test_splits - Splits test file into multiple smaller files, but file sizes are not evenly distributed

3. user_attributes - Added new attributes for user views, purchase instances and total purchases

4. output_rating_pred_to_kaggle_format - Added code to create numpy arrays for user / coupon hash and IDs

5. average_output_rating_pred*** - Outputs average of two prediction files

6. Output_item_rec_toKaggle_format - Converts output from MML item recommendation too to Kaggle format

DataCentric1/ponpare