04d9ad51d1
Remove Tensorflow from docs + code ( #1289 )
2026-01-08 20:25:06 -08:00
980c6ddc07
Extend package support Python 10-14 + relax dependencies ( #1276 )
2026-01-07 14:11:40 -08:00
0167accd0a
license ( #1263 )
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change license to Apache 2.0
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Co-authored-by: Anish Athalye <me@anishathalye.com >
2025-12-15 16:56:30 -08:00
e4be990d65
Add clarifying comment
2024-07-08 23:08:56 -07:00
00ae7c83b2
Fix comment formatting
2024-07-08 23:02:46 -07:00
c72f0c2cdf
Remove deprecated multi_class argument in LogisticRegression and skip test for sklearn 1.5.0 regression ( #1124 )
2024-05-24 19:48:04 +00:00
7d1f335017
Improve performance of find_label_issues for segmentation ( #1067 )
2024-04-10 21:09:28 +00:00
ae085b45b5
ensure near-predicted labels are not flagged as label issue ( #950 )
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* ensure near-predicted labels are not flagged as label issue
2024-01-10 11:39:28 +05:30
e90dea60c7
702 - Shorten Refs of classes and functions ( #831 )
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Co-authored-by: Elías Snorrason <eliassno@gmail.com >
Co-authored-by: tataganesh <tataganesh95@gmail.com >
2023-12-07 13:37:16 +00:00
6d45971cf8
List comprehension to numpy ops for efficiency ( #844 )
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Co-authored-by: Elías Snorrason <eliassno@gmail.com >
2023-09-20 19:19:51 +00:00
cb4c05cbff
Add support for high dimensional arrays in CleanLearning( #749 )
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Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
Co-authored-by: Hui Wen <45724323+huiwengoh@users.noreply.github.com >
2023-06-27 00:12:52 -04:00
860bd6f551
Dont print recompute joint warning when estimation_method = off_calibrated_custom ( #746 )
2023-06-18 17:02:51 -07:00
00776646a7
Fix bug with call to find_overlapping_issues without specifying labels ( #652 )
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* fix None labels issue
* build: ➕ add hypothesis to dev dependencies. Used for property-based testing
* test: ✅ test that find_overlapping_classes can run by only providing a confident joint
Resolves #651
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Co-authored-by: Elías Snorrason <eliassno@gmail.com >
2023-03-13 15:37:00 +00:00
70a2ed2fa2
Add clipping of small probabilities to address issue #639 ( #647 )
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Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
2023-03-12 20:51:03 -07:00
dbc87116ea
Documentation improvements ( #643 )
2023-02-28 16:06:17 -08:00
0c02ec953b
Add two methods to filter.find_label_issues ( #595 )
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"low_self_confidence" or "low_ normalized_margin"
Co-authored-by: huiwengoh <45724323+huiwengoh@users.noreply.github.com >
Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
2023-01-31 23:26:20 -08:00
888246e2d5
Improve num_label_issues usage of confident_joint to match find_label_issues ( #610 )
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Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
2023-01-27 14:47:02 -08:00
7b589f6d63
updating copyright year to include 2023 ( #594 )
2023-01-06 21:25:57 -08:00
a222859569
Improve docs in label error detection methods for classification data + filter/count mypy type annotations ( #543 )
2022-11-23 23:01:36 -08:00
f37ba9ff39
support missing classes in multilabel tasks ( #523 )
2022-11-04 15:00:43 -07:00
cbe3ce0f20
move multilabel functions to utils ( #515 )
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Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
2022-11-03 10:16:28 -07:00
c2d319d0ed
Add support for missing classes ( #511 )
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Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
2022-10-31 16:23:41 -07:00
b12d76b6d1
Multilabel code restructuring with aggregation/scorer functions ( #509 )
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_find_label_issues_multilabel uses EMA instead of mean-pooling when computing label quality scores
Co-authored-by: Elías Snorrason <eliassno@gmail.com >
Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
2022-10-28 16:26:39 -07:00
e060f551fb
supporting multilabel via one-vs-rest reductions ( #483 )
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Co-authored-by: Elías Snorrason <eliassno@gmail.com >
Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
2022-10-17 12:09:23 -07:00
57bcfd0a99
Mypy typechecking fix for num_label_errors ( #500 )
2022-10-07 19:43:40 -07:00
2906bf6292
Update # issues returned by num_label_issues ( #485 )
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* Added code and test for returning correct num label issues
* Fixed docstring
* Addressed mypy uncertain typing issue
* Added typing and typing checks
* Addressed PR comments
2022-10-05 20:55:49 -07:00
57adf33369
Adding pylint CI checks ( #465 )
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* Update ci.yml
* remove unused import
* 💚 merge pylint jobs
* 🔧 add .pylintrc
* 🚨 handle pylint errors
Co-authored-by: Elías Snorrason <eliassno@gmail.com >
2022-09-23 16:10:03 +00:00
1b813d9666
fix bug in hard-coded test. generalize the test ( #448 )
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* fix bug in hard-coded test. generalize the test
* 🐛 cast rounded num_issues to int
np.rint outputs an array of the same shape and type as its input. num_label_issues is expected to return an integer.
Co-authored-by: Elías Snorrason <eliassno@gmail.com >
2022-09-15 18:16:56 -04:00
3ff8fab2d9
make num_label_issues = cj calibrated offdiag sum ( #445 )
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The discrepancy occurs because cj calibrated maintains a guarantee that it will perfectly count every example in the dataset (assumes no out of distribution examples).
You can see this when by following this change of methods:
* see `calibrate_confident_joint`, specifically this line here: https://github.com/cleanlab/cleanlab/blob/master/cleanlab/count.py#L172
* round here https://github.com/cleanlab/cleanlab/blob/9240a8c56d020abec8566a0a56d22dcb99d32528/cleanlab/internal/util.py#L209
* the actual rounding occurs here https://github.com/cleanlab/cleanlab/blob/9240a8c56d020abec8566a0a56d22dcb99d32528/cleanlab/internal/util.py#L174
the fix to make `num_label_issues` the same is just to round instead of flooring.
see the two GREEN columns in the attached image
> [nit] consider `np.rint()` instead of `np.round()` for clarity
good call. updated
2022-09-15 11:44:27 -07:00
a4ad6460a2
Format return docstrings and add typing ( #437 )
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* typing and return docstrings
* address typing complaints
* allow redefinition
* typing complains for pandas
* .values -> to_numpy()
2022-09-15 11:46:14 +00:00
3fb4133a5c
np.array to np.ndarray
2022-08-09 03:30:57 -04:00
72d6c73a94
Clarify shapes of matrices in cj_multi_label
2022-08-09 03:25:03 -04:00
c0fe76c098
Changed all docstring instances of np.array to np.ndarray ( #336 )
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* Changed all instances of np.array in docstring to np.ndarray
* np.array is NOT a proper class name it is just a function to
create np.ndarrays and therefore should not be parameter class
* Black formatting compliance
2022-08-08 23:30:12 -07:00
b93fdebf30
Add compatibility for tensorflow and pytorch Dataset objects ( #311 )
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* validation_func docstring
* torch,tf compatibility+tests
* keras test
* skip tests if python < 3.7
* pytorch numpy int bug on windows
* make tensorflow test work on windows
* move tf env variable setting
* pytorch test increase epochs
* install cpu-tensorflow on windows CI
* torch test optimizer to adam
* fix bugs in shuffled TF dataset
* dummy unit test for TF on windows
* dummy code for TF windows testing
* deal with np.int bug on windows
* remove windows debugging code
* docstrings for new functionality
* address merge conflicts
* reformat after merge
* addressed comments
2022-07-27 21:42:13 -07:00
6c6c13664e
Standardize naming on K, num_classes and N, num_examples ( #312 )
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* update N in classification.py
* minor docstring changes on K-1 classes
* use K in shape
* minor grammar fixes
* docs language improvements
Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com >
2022-07-18 18:50:17 -07:00
9c543c6cba
error for missing classes, consistency on determining num_classes, code cleanup ( #308 )
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* edge cases
* unique_classes in get_confident_thresholds
2022-07-12 14:45:20 -07:00
0705ff2d0a
Add static type checking
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Our package doesn't have type annotations everywhere, so we can't use
mypy in strict mode just yet. Still, adding type checking in CI is
valuable, so we don't have unchecked annotations in our code.
This patch includes basic fixes to make type checking pass, including
switching the incorrect `np.array` type annotation for `np.ndarray` and
adding some assertions for flow-sensitive typing.
2022-07-06 17:21:56 -04:00
f62bc36e54
Allow CleanLearning to use validation data in each fold ( #295 )
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* allow CleanLearning to use val data in each fold
* add unittest for using val data in CleanLearning
2022-06-28 22:04:22 -07:00
ffd6fc1b35
Make CleanLearning work with pandas and other non-numpy feature objects X ( #285 )
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* 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 >
2022-06-24 04:01:55 -07:00
af11106e77
Clarify labels format ( #282 )
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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
2022-06-20 12:58:24 -07:00
eb54447901
Change shape (N, ) back to (N,) to adhere to numpy standard
2022-06-20 11:10:00 -07:00
25036dc48e
clarify expectation for labels
2022-06-20 10:32:28 -07:00
5bbea05992
Replace shape (N,) with (N, ) everywhere
2022-06-20 10:30:12 -07:00
1f40bdcd67
clarify all labels must be present in docstring
2022-06-19 16:00:51 -07:00
670d9d680e
use shape[1] instead of unique everywhere. replace K with num_classes
2022-06-19 15:56:13 -07:00
fc0db77892
remove unused code and unused param in docstring
2022-06-19 15:46:52 -07:00
215945f690
Remove redundant code. replace unique with pred_prob shape 1
2022-06-19 15:45:29 -07:00
7aa34a33ba
Fix bug. get thresholds broken for multi_label
2022-05-20 21:55:32 -04:00
e971350795
Clarify and fix several docstrings. ( #214 )
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* Clarify and fix several docstrings.
* Adjustments based on Jonas's comments.
* fix typo
2022-04-15 19:06:45 -04:00
269a09d1b3
Fix error in docstring. missing item in tuple
2022-04-13 21:17:22 -07:00
Ulyana