Fix postprocessing on binary feature columns with number dtype

[geoffreyangus]

This PR ensures that the postprocessing behavior before #2058 is preserved when dealing with binary feature columns of dtype float/int. This is done primarily by reverting the changes introduced by #2058 in ludwig/features/binary_feature.py and ludwig/visualize.py. You can see the full changes in binary_feature.py and visualize.py relative to 0.5.2 here and here, respectively.

That said, in order to achieve this, we add several checks upstream in cast_column to ensure that the old behavior when determining dtypes is preserved. The one caveat is that this requires calling compute(), which could be expensive in large datasets.

[github-actions]

Unit Test Results

       6 files  ±  0         6 suites  ±0   2h 22m 4s ⏱️ + 5m 30s
2 846 tests +  6  2 812 ✔️ +  7    34 💤 ±0  0 ❌  - 1 
8 538 runs  +18  8 432 ✔️ +19  106 💤 ±0  0 ❌  - 1 

Results for commit eb78129. ± Comparison against base commit 36787ba.

♻️ This comment has been updated with latest results.

[justinxzhao]

Code LGTM. Not totally sure why this change would causes tests to be flaky.