MLJ.jl Versions Save

MLJ v0.20.3

Diff since v0.20.2

• Bump compat for MLJFlow to 0.4 to buy into MLJBase.save method ambiguity fix (in MLJFlow 0.4.1).

Merged pull requests:

• Clarify input_scitype for Static models (#1076) (@ablaom)
• Documentation updates (#1077) (@ablaom)
• Add integration tests (#1079) (@ablaom)
• Test new integration tests. No new release. (#1080) (@ablaom)
• Fix the integration tests (#1081) (@DilumAluthge)
• Move EvoLinear into [extras] where it belongs (#1083) (@ablaom)
• CI: split the integration tests into a separate job (#1086) (@DilumAluthge)
• CI tweaks (#1087) (@ablaom)
• Update list_of_supported_models for betaml (#1089) (@sylvaticus)
• Update ModelDescriptors.toml for BetaML models (#1090) (@sylvaticus)
• Update documentation to reflect recent BetaML reorganisation (#1091) (@ablaom)
• Replace relevant sections of manual with links to the new MLJModelInterface docs. (#1095) (@ablaom)
• Update docs. No new release (#1096) (@ablaom)
• Update getting_started.md to avoid error from line 338 (#1098) (@caesquerre)
• For a 0.20.3 release (#1102) (@ablaom)

Closed issues:

• Meta issue: lssues for possible collaboration with UCL (#673)
• Integration test failures: Classifiers (#939)
• Oversample undersample (#983)
• Add AutoEncoderMLJ model (part of BetaML) (#1074)
• Add new model descriptors to fix doc-generation fail (#1084)
• Update list of BetaML models (#1088)
• Upate ROADMAP.md (#1093)
• Deserialisation fails for wrappers like TunedModel when atomic model overloads save/restore (#1099)

MLJ v0.20.2

Diff since v0.20.1

• Replace MLFlowLogger with MLJFlow.Logger; see here. So a logger instance is now instantiated with using MLJFlow; logger = MLJFlow.Logger(baseuri). This is technically breaking but not tagged as such, because MLFlow integration is still experimental.

Merged pull requests:

• Fix MLJTuning.jl links (#1068) (@jd-foster)
• CompatHelper: add new compat entry for Statistics at version 1, (keep existing compat) (#1070) (@github-actions[bot])
• Bump compat: MLJFlow 0.3 (#1072) (@ablaom)
• For a 0.20.2 release (#1073) (@ablaom)

Closed issues:

• Export the name MLJFlow (#1067)
• evaluate errors (#1069)

MLJ v0.20.1

Diff since v0.20.0

• (new feature) Add the BalancedModel wrapper from MLJBalancing.jl (#1064)
• (docs) Add the over/undersampling models from Imbalance.jl to the Model Browser (#1064)

Merged pull requests:

• Add MLJBalancing to MLJ and add class imbalance docs (#1064) (@ablaom)
• For a 0.20.1 release (#1065) (@ablaom)

Closed issues:

• Oversampling and undersampling (#661)
• [Tracking] Migration of measures MLJBase.jl -> StatisticalMeasures.jl (#1053)
• Include MLJBalancing.jl in MLJ and re-export it's names. (#1062)
• Update docs for new class imbalance support (#1063)

MLJ v0.20.0

Diff since v0.19.5

• (breaking) Adapt to the migration of measures from MLJBase.jl to StatisticalMeasures.jl (#1054). See the MLJBase 1.0 migration guide for details.

Merged pull requests:

• CI: fix the YAML syntax for the docs job, and thus properly surface any docbuild failures (#1046) (@DilumAluthge)
• Update docs (#1048) (@ablaom)
• Try again to generate the documentation (#1049) (@ablaom)
• docs/make.jl: set devbranch to master, which means that the docs will be deployed for pushes to `master (#1051) (@DilumAluthge)
• Try to deploy docs again x 3 (#1052) (@ablaom)
• Adapt to migration of measures MLJBase.jl -> StatisticalMeasures.jl (#1054) (@ablaom)
• For a 0.20 release (#1060) (@ablaom)

Closed issues:

• Julia crashes when fitting a SVC (#1030)
• Update deprecated document example in "Transformers ..." section of manual (#1040)
• fit! not exported in 0.19.3/0.19.4? (#1041)
• Doc generation is failing silently (#1045)

MLJ v0.19.5

Diff since v0.19.4

• Correct problem with previous version in which some methods were not exported, namely: source, node, fit!, freeze!, thaw!, Node, sources, origins (#1043) @pebeto

Closed issues:

• Is the Averager documentation deprecated? (#1039)

Merged pull requests:

• Adding necessary exports (#1043) (@pebeto)
• For a 0.19.5 release (#1044) (@ablaom)

MLJ v0.19.4

Diff since v0.19.3

Merged pull requests:

• Updating MLJBase.jl dep to last version (#1037) (@pebeto)

MLJ v0.19.3

Diff since v0.19.2

Closed issues:

• SymbolicRegression.jl — registry update (#1032)

Merged pull requests:

• feat: Update ROADMAP.md be more understandable (#1031) (@MelihDarcanxyz)
• add sirus.jl and symbolicregression.jl models to model browser (#1033) (@OkonSamuel)
• Add MLJFlow for integration with MLflow logging platform (#1034) (@ablaom)

MLJ v0.19.2

Diff since v0.19.1

Closed issues:

• @from_network does more strange eval stuff (#703)
• Create new package for MLJ-universe-wide integration tests (#885)
• Stack of TunedModels (#980)
• Please add CatBoost or any alternate package (pure Julia) which can beat it (#992)
• Update list of models for BetaML (#993)
• Update List of Supported Models Clustering.jl Section (#1000)
• predict should work on DataFrameRow (#1004)
• Documentation generation fails silently (#1007)
• Clarify and fix documentation around reformat. (#1010)
• Reporting a vulnerability (#1015)
• What causes the Distributed.ProcessExitedException(3) error in Julia and how can I resolve it in my Pluto notebook? (#1018)
• Add link to Mt Everest blog (#1021)
• Remove "experimental" label for acceleration API docs (#1026)

Merged pull requests:

• Fix TransformedTarget example in manual (no new release) (#999) (@ablaom)
• updating Clustering.jl model list to address #1000 (#1001) (@john-waczak)
• Add CatBoost to list of models and 3rd party packages (#1002) (@ablaom)
• Some small documentations improvements. Not to trigger a new release. (#1003) (@ablaom)
• Add auto-generated Model Browser section to the manual (#1005) (@ablaom)
• Add new auto-generated Model Browser section to the manual. Not to trigger new release. (#1006) (@ablaom)
• Add Model Browser entry for SelfOrganizingMap (#1008) (@ablaom)
• Update documentation (#1009) (@ablaom)
• Clarify data front-end in docs (#1011) (@ablaom)
• Doc fixes. No new release. (#1012) (@ablaom)
• Update model browser and list of models to reflect addition of CatBoost.jl and some OutlierDetectionPython.jl models (#1013) (@ablaom)
• Update to the manual. No new release. (#1014) (@ablaom)
• Make docs fail on error (#1017) (@rikhuijzer)
• Cleaned up Adding Models for General Use documentation (#1019) (@antoninkriz)
• CompatHelper: bump compat for StatsBase to 0.34, (keep existing compat) (#1020) (@github-actions[bot])
• Remove CatBoost.jl from third party packages (#1024) (@tylerjthomas9)

MLJ v0.19.1

Diff since v0.19.0

Closed issues:

• Support for ProbabilisticSet type in MLJModelInterface.jl (#978)
• question about Isotonic Regression (#986)
• predict_mode of pipeline model return a UnivariateFinite after upgrade to 0.19.0 (#987)
• MLJ Tuning optimizers are no working with julia 1.8.3 and julia 1.9.0 (#990)
• WARNING: both MLJBase and DataFrames export "transform"; uses of it in module Main must be qualified (#991)
• CURANDError: kernel launch failure (code 201, CURAND_STATUS_LAUNCH_FAILURE) (#997)

Merged pull requests:

• Document changes and sundries. No new release. (#985) (@ablaom)
• (re) updated model names of BetaML (#994) (@sylvaticus)
• Exclude bib, md, and drawio from repo stats (#995) (@rikhuijzer)
• For a 0.19.1 release (#998) (@ablaom)

MLJ v0.19.0

Diff since v0.18.6

MLJBase compatibility is bumped to 0.21 and MLJModels compatibility is bumped to 0.16. This makes a new simplified method for exporting learning networks available but also introduces some breaking changes:

• (mildy breaking) The value method is no longer exported by MLJ as essentially private (#891)
• MLJBase 0.21 release notes
• MLJModels 0.16 release notes

Closed issues:

• Do not re-export value (#891)
• Large models name change in BetaML (#963)
• Add ConformalPrediction.jl to list of 3rd party packages (#967)
• Documentation for BinaryThresholdPredictor (#973)

Merged pull requests:

• Update docs for new learning network export method (#972) (@ablaom)
• added to docs (#979) (@pat-alt)
• For a 0.19 release (#984) (@ablaom)