Lightwood

Features:
* Simplified type mapping in Json AI (724)
* Setter for neural mixer epochs (737)
* Improved `nan` handling (720)
* Drop columns with no information (736)
* LightGBM mixer supports weights (749)
* Improved OneHot and Binary encoders' logic around weights (749)
* New accuracy function lookup hierarchy (754)
* Better warning logs when `nan` or `inf` values are encountered (754)

Bug fixes:
* Fixed LightGBM error on CPU (726)
* Cast TS group by values to string to avoid TypeError (727)
* Check target values when transforming time series if task requires them (747)
* Streamline encode/decode in `TsArrayNumericEncoder` (748)
* `target_weights` argument is now used properly (749)
* Use custom R2 accuracy to account for edge cases (754)
* Fixed target dropping behavior (754)

Other
* Update README.md example (731)
* Separate branch for docs (740)
* Docs for image and audio encoders; LightGBM and LinearRegression mixers (721, 722)

Many thanks to our community contributors for this release!
MichaelLantz mrandri19 ongspxm vaithak

Features:
* SHAP analysis block (679, mrandri19)
* Disable `GlobalFeatureImportance` when we have too many columns (681, ongspxm; 698)
* Added cleaner support for file path data types (image, audio, video) (675)
* Add `partial_fit()` to `sktime` mixer (689)
* Add `ModeEnsemble` (692, mrandri19)
* Add weighted `MeanEnsembler` (680, vaithak)

Bug fixes:
* Normalized column importance range (690)
* Fix ensemble supports_proba in calibrate.py (694, mrandri19)
* Remove self-referential import (696)
* Make a integration test for time_aim (685, MichaelLantz)
* Fix for various datasets (700)

Other
* Improve logging for analysis blocks (677; MichaelLantz)
* Custom block example: `LabelEncoder` (663)
* Implement ShapleyValues analysis (679)
* Move array/TS normalizers to generic helpers (702)

Many thanks to this month's community contributors!
alteregoprofile, LyndonFan, MichaelLantz, mrandri19, ongspxm

Features:
* MFCC-based audio encoder (625, 638; mrandri19)
* Quantum mixer (645, ongspxm)
* Identity encoders (623; LyndonFan)
* Simpler default splitter (624)
* `MeanEnsemble` (658; mrandri19)
* Improved interface to predict with all mixers (627)
* API: `predictor_from_json_ai` (633; mrandri19)
* One-hot encoder mode to work without unknown categories (639; mrandri19)
* System for handling optional dependencies (640)

Bug fixes:
* `Img2Vec` encoder bug fixes and tests (619, 622; mrandri19)
* Fix encoder prepare calls (630)
* Black formatter fix (650)
* Docs: `doc_build` triggers during `pull_request` (653, 665; MichaelLantz)
* `ArrayEncoder` fixes (604, alteregoprofile)

Other
* Rename `fit_on_validation` to `fit_on_all` (626)
* Smaller test datasets (631)
* Docs: add a time series forecasting tutorial (635)
* Improved documentation coverage (654, 660)
* Docs: `doc_build` automatically runs jupyter notebooks (657)

Features:
* Streamlined dynamic `.predict()` argument passing (563)
* Set default logging level with environment variable (mrandri19, 603)
* Colored logs (mrandri19, 608)

Bug fixes:

* `JsonAI` blocks are now `Module`s (569)
* Ignore column drop error if column is not in the dataframe (579)
* LightGBM dependency issue (609)

Other
* Introduction to statistical analyzer tutorial (577)
* Custom cleaner tutorial (581)
* Custom mixer tutorial (575)
* Custom analysis block tutorial (576)
* Docstring for `BaseEncoder` (587)
* Native Jupyter notebook support inside docs (586)
* Automated docs deployment (610)
* Updated CLA bot (612)
* Improved `README.md` and `CONTRIBUTING.md` (613)

Note: benchmarks will not run on the latest commit for this release, they were instead successfully ran for commit `79f27325a0877bb95709373007a97161fc9bb2eb `.

Features:
* Modular Cleaner (538 and 568)
* Modular Analysis (539)
* Better Imports (540)
* Improved Json AI default arguments (543)
* Add seed to splitter (553)
* Stratification and 3-way splitting (542, 571)
* Use MASE metric for TS model selection (499)

Bug fixes:

* Allow quantity as target (546)
* Fix for LightGBM device check (544)
* Select OneHotEncoder at Json AI build time and fix pd.None bugs (549)
* Miscellaneous fixes (570)

Other
* Improved CONTRIBUTING.md (550)

Features:
* Better defaults for Neural model in time series tasks (461)
* Seed keyword passed (482)
* Handle ' and " in dataset column names (503)
* Helper function to split grouped time series (501)
* Enhanced date-time + tag histograms (502)
* Nonconformist speed optimizations (497)
* Add `dtype.tsarray` (530)

Bug fixes:
* Fix analysis memory usage (485)
* Fix incorrect return value for order column in time series tasks (488)
* Fix time series encoding issue (495)
* Remove deprecated logic (518)
* Make explainer work with categorical targets not present in the training data (500)
* Fix sktime dependency (524)
* Better detection, cleaning and encoding of arrays (512)
* Use correct accuracy score for binary data (532)
* `allow_incomplete_history` for time series predictors (525)

Other
* Automated documentation (NOTE: still in beta; 519, 528)
* Rename `model` to `mixer`; `folds` to `subsets` (534)