v0.18.6

MLJ v0.18.6

Diff since v0.18.5

Closed issues:

• DBSCAN from Clustering.jl not registered (#845)
• Update manual re new reporting_operations trait (#956)
• Improvement in the Preparing Data part (#964)
• serializable and restore! should be "safe" to use any time (#965)
• Adds EvoLinearRegressor to list of models (#966)
• export InteractionTransformer from MLJModels (#969)
• Encoders for feature engineering (#970)
• Clarify meaning of "table" in documentation (#971)
• re-export serializable and restore! (#975)

Merged pull requests:

• Updated names of BetaML models (#968) (@sylvaticus)
• add the interface package to add (#974) (@xgdgsc)
• Minor doc improvements and new exports (#976) (@ablaom)
• For a 0.18.6 release (#977) (@ablaom)

v0.18.5

MLJ v0.18.5

Diff since v0.18.4

Merged pull requests:

• Fix mini typos in docs (#958) (@svilupp)
• Documentation updates (#959) (@ablaom)
• Bump version (#961) (@jbrea)
• For a 0.18.5 release (#962) (@ablaom)

v0.18.4

MLJ v0.18.4

Diff since v0.18.3

Closed issues:

• Tutorial not working (#951)
• Bump MLJBase compat and re-export feature_importances (#954)

Merged pull requests:

• Update link for telco example to Data Science Tutorials version (#952) (@ablaom)
• Update API spec re training losses and feature importances (#953) (@ablaom)
• For a 0.18.4 release (#955) (@ablaom)

v0.18.3

MLJ v0.18.3

Diff since v0.18.2

Closed issues:

• Feature request: ability to convert scitype warnings into errors (#908)
• Confusing true_negative(x, y) error (#919)
• Show is too long for MulticlassPrecision and MulticlassTruePositiveRate (#923)
• DOC: Link giving 404 not found (#929)
• Re-export scitype_check_level (#936)
• models(matching(X, y)) returns empty but shouldn't (#937)
• LoadError on Getting Started Fit and Predict exercise (#940)
• Change in Julia version generating the Manifest.toml 's ? (#941)
• export PerformanceEvaluation (#944)
• Make docs regarding Random Forest and Ensebles more clear (#945)
• Compile time for DataFrames, typename hack not working (#946)
• Factor out performance evaluation tools (#947)

Merged pull requests:

• Fix level of confidence interval in telco example to make it 95% (#938) (@ablaom)
• Update the list of models in the manual (#942) (@ablaom)
• Re-export default_scitype_check_level (#943) (@ablaom)
• Clarify homogeneous ensembles comments (#948) (@ablaom)
• For a 0.18.3 release (#949) (@ablaom)

v0.18.2

MLJ v0.18.2

Diff since v0.18.1

Closed issues:

• Update Save method documentation (#899)
• DOC: Link giving 404 not found (#929)
• Question about using acceleration to implement parallelism (#934)

Merged pull requests:

• Fix a table in telco tutorial (#927) (@ablaom)
• add MLCourse (#928) (@jbrea)
• Add link to MLCourse in the documentation (#930) (@ablaom)
• Move EPFL course up the list on "Learning MLJ" page (#931) (@ablaom)
• Add OneRuleClassifier to list of models in manual (#932) (@ablaom)
• For a 0.18.2 release (#935) (@ablaom)

v0.18.1

MLJ v0.18.1

Diff since v0.18.0

• Re-export doc from MLJModels and bump compat of same

Merged pull requests:

• For a 0.18.1 release (#926) (@ablaom)

v0.18.0

MLJ v0.18.0

Diff since v0.17.3

This release supports changes appearing in the upstream package releases
listed below (click on package for detailed release notes).

The principal change, which is breaking, is how model
serialization works. The previous MLJ.save method still works, but
you can only save to Julia JLS files, and the format is
new and not backwards compatible. A new workflow allows for
serialization using any generic serializer; serialization now plays
nicely with model composition and model wrappers, such as TunedModel
and EnsembleModel (even with non-Julia atomic models),
and training data will not be inadvertently serialized.

Refer to this manual page details.

• MLJBase 0.20
• MLJTuning 0.7
• MLJEnsembles 0.3
• MLJIteration 0.5

The package MLJSerialization has been dropped as a dependency as
serialization functionality has moved to MLJBase.

Closed issues:

• Use of ScientificTypes and CategoricalArrays in native model (#907)
• Broken tutorial link (#917)
• For a 0.18 release (#920)

Merged pull requests:

• More doc updates and new example (#914) (@ablaom)
• Documentation update. No new release. (#916) (@ablaom)
• Address changes in MLJBase 0.20 (#921) (@ablaom)
• Update manual to reflect changes in MLJBase 0.20 (#922) (@ablaom)
• For a 0 point 18 release (#924) (@ablaom)
• For a 0.18 release (#925) (@ablaom)

v0.17.3

MLJ v0.17.3

Diff since v0.17.2

Merged pull requests:

• Add documentation for the new model docstring standard (#906) (@ablaom)
• For a 0.17.2 release (#912) (@ablaom)

v0.17.2

MLJ v0.17.2

Diff since v0.17.1

Closed issues:

• Discussion: Outlier Detection API in MLJ (#780)
• Is MLJ ready for Julia 1.7? (#869)
• Documentation of 'Common MLJ Workflows' shows wrong partition syntax (#894)
• [Discussion] Review model documentation strings (#898)
• Update list of models in docs for MLJText model change (#900)
• Proposal for new Model docstrings standard (#901)

Merged pull requests:

• Documentation fix. No new release (#895) (@ablaom)
• Explain outlier detection models (#896) (@davnn)
• Update list_of_supported_models.md (#897) (@zsz00)
• Remove binder notebook from readme and documentation (#902) (@ablaom)
• BagOfWordsTransformer -> CountTransformer in List of Models (#903) (@ablaom)
• A number of documentation updates. No new release. (#904) (@ablaom)
• Tweak docs for nodes (#905) (@ablaom)
• Export UnivariateFillImputer (#909) (@ablaom)
• For a 0.17.2 release (#910) (@ablaom)

v0.17.1

MLJ v0.17.1

Diff since v0.17.0

• Programatically export all measure types, aliases and instances, which catches a few previously missed cases (#892)
• Programatically export almost all model and measure traits (#892)
• Bump MLJBase requirement to ensure built-in measure instances (eg log_loss) have doc-strings.

Closed issues:

• Extend model serialization to composite models with a components needing specialised serialization (#678)
• New measures RSquared and aliases rsq, rsquared need exporting (#880)
• Re-export all traits. (#888)
• What does MLJ.save really save? (#889)
• Programmatically re-export measures and their aliases from MLJBase (#890)

Merged pull requests:

• Fix typos in Getting Started (#881) (@takuti)
• Typos in docs. No new release. (#882) (@ablaom)
• Fix MLJFlux.jl project URL (#883) (@i-aki-y)
• Broken link fixes in docs. No new release. (#884) (@ablaom)
• Update examples/lightning_tour/ for MLJ 0.17 (#886) (@ablaom)
• Added recent measures to src/MLJ.jl (#887) (@sayantan1410)
• Clean up export of measure-related methods (#892) (@ablaom)
• For a 0.17.1 release (#893) (@ablaom)