Releases: alan-turing-institute/MLJ.jl
Releases · alan-turing-institute/MLJ.jl
v0.20.3
MLJ v0.20.3
- 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 overloadssave/restore
(#1099)
v0.20.2
MLJ v0.20.2
- Replace
MLFlowLogger
withMLJFlow.Logger
; see here. So a logger instance is now instantiated withusing 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:
v0.20.1
MLJ v0.20.1
- (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:
v0.20.0
MLJ v0.20.0
- (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
: setdevbranch
tomaster
, 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:
v0.19.5
v0.19.4
MLJ v0.19.4
Merged pull requests:
v0.19.3
MLJ v0.19.3
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)
v0.19.2
MLJ v0.19.2
Closed issues:
@from_network
does more strangeeval
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 onDataFrameRow
(#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)
v0.19.1
MLJ v0.19.1
Closed issues:
- Support for
ProbabilisticSet
type inMLJModelInterface.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
, anddrawio
from repo stats (#995) (@rikhuijzer) - For a 0.19.1 release (#998) (@ablaom)
v0.19.0
MLJ v0.19.0
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: