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Releases: mindsdb/lightwood

Release 22.7.2.0

11 Jul 20:18
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Release 22.7.2.0

Benchmarks

Features

  • Experimental N-HITS forecasting mixer (#886)
  • Differencing blocks for time series tasks (#903)
  • Linear tree for LightGBMArray mixer (#902)
  • STL decomposition blocks for time series tasks (#907)

Fixes

  • Restored statsforecast as default backend for ARIMA models (#904)

Other

N/A

Release 22.6.1.2

03 Jun 14:48
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Changelog

Features

Fixes

Other

Benchmarks:

Release v22.5.1.0

06 May 16:13
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Changelog:

Features

  • #865 - ProphetMixer to forecast

Bug fixes

  • #866 & #872 - Fix TS float cleaner can't deal with malformed input
  • #873 - Fix non-null TS delta analysis

Other

Benchmarks

Release v22.4.1.0

01 Apr 16:00
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Lightwood 22.4.1.0 changelog:

Features: -

Bug fixes:

  • #848 - Log runtime per mixer
  • #855 - Fix dimension error in neural mixer

Other

  • #850 - Restore Windows CI

Full Changelog:

b05e8b4...v22.4.1.0

Release 22.2.1.0

03 Feb 23:11
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Lightwood 22.2.1.0 changelog:

Features:

  • Simpler and better Json AI #826
  • Compute & log time per phase #828

Bug fixes: -

Other:

  • Remove anomaly_error_rate arg in favor of fixed_confidence #825

Full Changelog: v22.1.4.0...v22.2.1.0

Release 22.1.4.0

27 Jan 13:21
0d8e420
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Lightwood 22.1.4.0 changelog:

Moving forward, our release versioning schema will follow this format:
[year's last two digits].[month].[week].[patch]

(note: other MindsDB repositories will also switch to this)

Features:

  • ConfStats block (#800): provides calibration insights for the lightwood predictor
  • Temperature scaling block (#795, experimental & non-default): alternative to ICP block for confidence estimation
  • Improved documentation pages (#806)
  • Replaced default encoder for time series forecasting tasks (from RNN to simple MA features, #805)
  • Explicit detrend and deseasonalize options for sktime mixer (#812)

Bug fixes:

  • Updated update model tutorial (#774)
  • Fix forecast horizon lower bound (#801)
  • Handle empty input when predicting (#811)

Other

  • Rename nr_predictions parameter to horizon (#803)
  • Set allow_incomplete_history to True by default (#818)

Full Changelog

v1.9.0...v22.1.4.0

Release 1.9.0

27 Dec 21:06
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Lightwood 1.9.0 changelog:

Features:

  • Improved T+N forecast bounds (#788)
  • Optimized classifier ICP block for confidence estimation (#798)

Bug fixes:

  • Fixed initialization issues in confidence normalizer (#788)
  • Fixed no analysis mode (+ parameter to specify this in a problem definition, #791)
  • Fixed temporal delta estimation for ungrouped series (#792)

Other

  • Add original query index column in output (used internally in MindsDB, #794)
  • Streamlined explain() arg passing #797

Release 1.8.0

22 Dec 17:24
76e1118
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Lightwood 1.8.0 changelog:

Features:

  • SkTime mixer 2.0 (#758, #767)
  • Improve time aim feature (#763)
  • Improved OHE and binary encoders, standardized a few more (#755, #785)
  • Streamlined predictor.adjust signature (#762)
  • Add precision, recall, f1 (#776)

Bug fixes:

  • Do not drop single-group-by column (#761, #756)
  • OH and Binary Encoders weighting fix (#769)
  • LGBM array mixer does not modify the datasource (#771)
  • Fixes missing torchvision import (#784)

Other

  • Make image encoder optional (#778)
  • Revamp notebooks test docs (#764)

Release 1.7.0

17 Nov 22:24
3eccb43
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Lightwood 1.7.0 changelog:

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)

Release 1.6.0

01 Nov 23:26
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Lightwood 1.6.0 changelog:

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)