* Create FAQ page in cleanlab docs
* Add FAQ notebook to store answers to frequently asked questions
* Improved formatting issues for faq page
- added faq to sidebar
* Improved formatting issues for faq page
- added faq to sidebar
- changed email to comply with CLA
* Removed faq numbering
- Removed notebook output metadata
- Added notebook to index for left table link
* Text and example rewritten for clarity
- How do I format labels for cleanlab-- example improved
- How do I format labels for cleanlab-- text amended
- Can't find an answer to your question-- added links
* add links to issues/slack
Co-authored-by: Ulyana Tkachenko <uly@ulyana.lan>
Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com>
* cleanlearning w dfs
* work for sparse matrix as well
* simplify logic of labels_to_array and extend types
* address pr feedback
* add unit test
* rare label dataframe
* modularize subsetting code
* series rarelabel test
* replace cal.com with slack/email
* Add general method to find num_classes from labels
* compute num_classes with pred_probs.shape[1]
* fix broken commits, address 2nd round of comments
Co-authored-by: Curtis G. Northcutt <curtis.northcutt@gmail.com>
Add clarification of the labels format requirements for all major API functions.
* Fix broken link
* Clarify reqs for labels format. rank.py does not yet support multi_label
* add double ticks to code in docstrings
* clarify docstring
* further clarify multi_label vs single label labels reqs
* also add new docstring to confident joint
* example label formatting
* example label format in text tutorial
* example label format for tabular tutorial
* y -> full_labels
* example label format for audio tutorial
* clarify input shapes in image tutorial
* clarify input shapes in text tutorial
* clarify input shapes in tabular tutorial
* clarify input shapes for audio tutorial
* Add KNN distance OOD scoring function and unit tests
* Update KNN distance OOD scoring function
* Change query_features to features in unit tests for KNN distance OOD scoring function
* Update KNN distance OOD scoring function
* Update tests for KNN distance OOD scoring function to use auto for algo
* Allow k=None for KNN Distance OOD score
* added class to use cleanlab with tensorflow and huggingface models
* - Documentation refactoring
- predict and predict_proba functions work on new test data too
* Add log_loss_search weighting method for ensemble label quality scoring function
* Update log_loss_search weighting method
* Add test for log_loss_search method
* Add parameter to Ensemble label quality scoring function for t values in log_loss_search method
* Update ensemble label quality scoring function docstring
* Update ensemble label quality scoring function comments
* Update docstring in ensemble label quality scoring function
* Update docstring in ensemble label quality scoring function
* Update docstring in ensemble label quality scoring function
* Modify verbose printout for log_loss_search
* Add clipping of pred_prob when calculating weights for log_loss_search
* Add clipping of pred_prob and renormalization when calculating weights for log_loss_search
* Add comments for log_loss_search weighting scheme
The issue that was introduced in coverage 6.3 has been fixed:
https://github.com/nedbat/coveragepy/issues/1310#issuecomment-1129894701.
We can't just upgrade to `coverage` or `coverage>=6.4` because the
former could install bad versions of coverage (e.g. 6.3), and the latter
is unsupported on Python 3.6, which we want to continue supporting.
This patch just bans coverage 6.3 / 6.3.x, so with Python 3.7+, we'll
use the latest version of coverage, and with Python 3.6, we'll use the
latest supported version of coverage that's not a 6.3 release.
For some reason, GitHub is returning a 403 to the GitHub actions runner
when it tries to access these URLs. Maybe docs.github.com doesn't allow
access from GitHub actions.
* Allow user to pass custom_weights to ensemble scoring method
* Add tests for ensemble scoring with custom_weights
* Add check to make sure length of custom_weights matches len(pred_probs_list)
* Update tests for usage of custom_weights in ensemble scoring
Ulyana