This belongs to a McGill University project. The related dataset modification tool can be found in elements72/ECSE-557-project
Warning: enum_str does enumerate just fine, but in the case of binned/grouped values, they are still not ordered...
Datasets can be found in /datasets
.
filename | description |
---|---|
full | original dataset as exported from kaggle |
base | blank ID for all entries. all following are based on base . Run enum on ID to set to 0 |
base_debiased | as many zero-targets as one-targets. training bias is too big otherwise. |
b_d_inc_* | base_debiased, but with income grouped to filename based bin size. Create using our tool. |
Executable python scripts can be found in the root directory, the are named according to the used dataset (see above table).
The print_b_d_json_accuracies.py
script is used to evaluate the json files logged by the b_d_inc_*
classifier and create confusion matrices used in the report.
Files that should not be ran directly (because they are internal libraries of sort) are
classifier.py
, providing the actual classifier codeconf_mat_plt.py
, a utility for creating a confusion matrix with matplotlib
The helpers
directory contains a script to create the base_debiased data set from base.