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Releases: adaptive-machine-learning/CapyMOA

v0.2.0

04 May 05:28
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v0.2.0
7fc2966
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v0.2.0

v0.2.0 (2024-05-04)

Documentation

  • docs: fix readme for pypi (9c7af27)

Feature

  • feat: add streaming random patches classifiers (5d3b877)

Fix

  • fix: updating tutorial 6

Fixing issues with tensorboard (95a4d54)

  • fix: updating notebooks and more

Updated all the tutorial notebooks.
AdaptiveRandomForest -> AdaptiveRandomForestClassifier.
Removed some outdated files (like accessing_sample_data.txt).
Removed outdated notebooks. (d1aef09)

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v0.1.1

03 May 07:28
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v0.1.1
1d1cd9f
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v0.1.1

v0.1.1 (2024-05-03)

Fix

  • fix: update pyproject.toml for initial release (cd7279c)
Assets 4
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v0.1.0

03 May 06:47
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v0.1.0
1a983a2
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v0.1.0

v0.1.0 (2024-05-03)

Build

  • build: remove river from default dependencies (66a3a21)

Ci

  • ci: publish to pypi (ec1256c)

  • ci: add gh-pages (6efd58c)

  • ci: doc error (7c1507f)

  • ci: doc error (678e0a2)

  • ci: doc error (3dda36c)

  • ci: Fix doc error (25b34df)

  • ci: rename SGBT to StreamingGradientBoostedTrees (82604a5)

  • ci: change python version of github actions to 3.9 (1a2ca36)

  • ci: only upload docs on push (f1f2416)

  • ci: add macos back to all_targets.yml (abe46f2)

  • ci: fix an off by one error in version numbers (9a8dbf1)

Documentation

  • docs: update README (01c4a9f)

  • docs: update landing pages (ee5eee4)

  • docs: fix spelling and style mistakes (95c72fb)

  • docs(SKClassifier): add docs, doctest, typehints, and minor refactor (d85b708)

Feature

  • feat: add missing datasets and document datasets (3ac973f)

  • feat: add online smooth boost classifiers (478bd93)

  • feat: add nochange and majority class classifiers (0c822c1)

  • feat: add OzaBoost (a08fd1b)

  • feat: improve capymoa environment configuration (ee96275)

  • feat: add SGBT (80f7007)

  • feat(EFDT): leaf_prediction as str

Users can still use leaf_prediction as an integer (0, 1 or 2), but it can also be used as a string:
"MajorityClass": 0, "NaiveBayes": 1, "NaiveBayesAdaptive": 2 (6454179)

  • feat(regressor): add SGDRegressor using sklearn (2e55155)

  • feat(regressor): add PassiveAggressiveRegressor (c54fe50)

  • feat(base): add SKRegressor (309aa48)

  • feat(SGDClassifier): add SGDClassifier (ec00ffd)

Fix

  • fix: update soknl and test (336766f)

  • fix: fix python 3.9 syntax error and float comparison in test (c7b7c1b)

  • fix: several updates

Updated EFDT and HoeffdingTree to
use _leaf_prediction(...) from _utils.py
Also changed dataset._util.py to
dataset.utils.py
Finally, updated the tests, there were
some issues (like EFDT_gini was using
InformationGain). (1dc6234)

Refactor

  • refactor(PassiveAggressiveClassifier): use SKClassifier base class (cb3ff18)

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Assets 2
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v0.0.1

29 Apr 21:22
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v0.0.1
8169a8e
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v0.0.1

v0.0.1 (2024-04-29)

Ci

  • ci: add conventional commit compliance check (136bad2)

  • ci(gh-actions): build release (f165dcc)

Documentation

  • docs(EFDT): Updating the EFDT documentation (362a510)

Fix

  • fix(EFDT): fixing error with leaf_prediction added in the previous change (a0bb50d)

Unknown

  • Added references in the documentation as well (5f4ba57)

  • Updating the documentation for ARF, ARFReg and EFDT (f9587c8)

  • Fix doc error (a3e00ce)

  • File Rename (f33c9da)

  • Addressing review comments (958456f)

  • Fix doc error (f7cffd1)

  • Split notebook 03_using_sklearn_pytorch.ipynb into 3:

  • 03_0_using_sklearn.ipynb

  • 03_1_using_pytorch.ipynb

  • 03_2_preprocess_using_MOA.ipynb

  • update README.md and invoke.yml (30dbbce)

  • Revert "Semver (#63)" (#64)

This reverts commit 4da804f. (9fa58a2)

  • Semver (#63)

  • build(pyproject.toml): add commitizen

  • build: use semantic release

  • build: temporarily add semvar as release branch

  • build: add package.json (4da804f)

  • Merge pull request #61 from hmgomes/update-270424

updating to the latest moa.jar (prediction intervals included) (21dfa76)

  • updating SOKNL test (59cea63)

  • updating to the latest moa.jar (prediction intervals included) (54aeac3)

  • Switch to dropbox for hosting (#59)

  • Switch to dropbox for hosting

  • Improve instructions for updating moajar (67ba9ad)

  • Add auto-download cli (#55) (2ae82ed)

  • Update contributing/docs.md (8d77f2b)

  • Merge pull request #53 from hmgomes/update-20-04-2024-extending-benchmark

Updates to benchmarking.py & adding knn (1647b09)

  • Merge pull request #52 from hmgomes/fix_get_moa_creation_CLI_function

Fix get moa creation cli function (ed2a164)

  • Merge pull request #47 from hmgomes/updates-18-04-2024

Removing CPSSDS for now (77aacfe)

Regression ensemble (8a4c955)

Fix benchmarking (1efab4e)

Updating notebooks to match new structure (205b23c)

  • Solving issues with test_ssl_classifiers.py (6c3d4e6)

  • Fixing test_batch.py issue (updating evaluation imports) (7efe451)

  • also removing it from the tests (b631eef)

  • Updating notebooks to use new project structure. (7ff90bd)

  • removing CPSSDS for now (b8955d8)

  • Merge pull request #40 from hmgomes/update-13042024

Updating notebooks, evaluation and visualization (8e11fb7)

  • Merge branch 'main' into update-13042024 (a9abb27)

  • Merge pull request #44 from tachyonicClock/restructure

Restructure (151db25)

  • Merge remote-tracking branch 'origin/main' into main

Conflicts:

src/capymoa/learner/regressor/regressors.py (eb36e60)

  • Merge branch 'main' into update-13042024 (cce9cc7)

  • Fix documentation build (2be493b)

  • Make learners private (b97db8c)

  • Use nitpicky sphinx build (eafe1b1)

  • Update documentation (576c907)

  • Split into one learner per file (6c35df9)

  • Run formatter and auto-fix lint issues (c2c320a)

  • Flatten modules (308e3de)

  • Add wrapper for naive bayes (#37)

  • Add a wrapper for naive bayes

Co-authored-by: Heitor Murilo Gomes <[email protected]> (c291381)

  • Fix tests (#43) (d8024d6)

  • add function for using wrappers as ensemble base learners and fixing parameter not working (3ea0ba8)

  • updating notebooks 00 and 01, and adding new visualization function. Some changes to evaluation.py as...

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