v0.8.8

MLJTuning v0.8.8

Diff since v0.8.7

• Change default logger from nothing to MLJBase.default_logger() (which can be reset with MLJBase.default_logger(new_logger)) #221

Merged pull requests:

• Make the global default_logger() the default logger in TunedModel(logger=...) (#221) (@ablaom)
• For a 0.8.8 release (#222) (@ablaom)

Closed issues:

• Use measures that are not of the form f(y, yhat) but f(fitresult) (#202)

v0.8.7

MLJTuning v0.8.7

Diff since v0.8.6

Merged pull requests:

• Overload constructor trait for TunedModel types (#219) (@ablaom)
• For a 0.8.7 release (#220) (@ablaom)

v0.8.6

MLJTuning v0.8.6

Diff since v0.8.5

• (new feature) Add logger option to TunedModel wrapper, for logging internal model evaluations to an ML tracking platform, such as MLflow via MLJFlow.jl. Default should be nothing for no logging (#193). The logger must support asynchronous messaging if TunedModel(model, ...) is specified with the option acceleration=CPUThreads() or CPUProcesses(). MLJFlow.jl 0.4.3 supports asynchronous messaging.

Merged pull requests:

• Adding loggers into TunedModels (#193) (@pebeto)
• For a 0.8.6 release (#218) (@ablaom)

Closed issues:

• Broken link (404) for each dependent link of the site https://alan-turing-institute.github.io (#217)

v0.8.5

MLJTuning v0.8.5

Diff since v0.8.4

• Write the PerformanceEvaluation objects computed for each model (hyper-parameter set) to the history, or write compact versions of the same (CompactPeformanceEvaluation objects) by providing TunedModel(...) a new option compact_history=true. The evaluation objects are accessed like this: evaluation = report(mach).history[index].evaluation, where mach is a machine associated with the TunedModel instance. For more on the differences between PerformanceEvaluation and CompactPerformanceEvaluation objects, refer to their document strings. (In MLJTuning 0.5.3 and 0.5.4 an experimental feature already introduced PerformanceEvalution objects to the history, but with no option to write the compact form. In the current release, compact objects are written by default.)

Merged pull requests:

• Create option to write CompactPerformanceEvaluation objects to history (#215) (@ablaom)
• For a 0.8.5 release (#216) (@ablaom)

v0.8.4

MLJTuning v0.8.4

Diff since v0.8.3

• (enhancement) Implement feature importances that expose the feature importances of the optimal atomic model (#213)

Merged pull requests:

• add feature importances support for tuned models (#213) (@OkonSamuel)
• For a 0.8.4 release (#214) (@ablaom)

v0.8.3

MLJTuning v0.8.3

Diff since v0.8.2

• Include full evaluation objects (key = :evaluation) in history entries (#210)

Merged pull requests:

• Add entire evaluation objects to history (#210) (@ablaom)
• For a 0.8.3 release (#212) (@ablaom)

v0.8.2

MLJTuning v0.8.2

Diff since v0.8.1

Merged pull requests:

• Overload save and restore (#208) (@ablaom)
• For a 0.8.2 release (#209) (@ablaom)

Closed issues:

• Overload save/restore to fix serialisation when atomic model has ephemeral fitresult (#207)

v0.8.1

MLJTuning v0.8.1

Diff since v0.8.0

Merged pull requests:

• Add prediction type check for Explicit strategy (#201) (@ablaom)
• Fix how measures are displayed on plot axes (#203) (@ablaom)
• For a 0.8.1 release (#204) (@ablaom)

v0.8.0

MLJTuning v0.8.0

Diff since v0.7.4

• (breaking) Bump MLJBase compatibility to version 1. When using without MLJ, users may need to explicitly import StatisticalMeasures.jl. See also the MLJBase 1.0 migration guide (#194)

Merged pull requests:

• Get rid of test/Project.toml (#190) (@ablaom)
• Fix some tests that use deprecated MLJBase code (#191) (@ablaom)
• Update code and tests to address migration of measures MLJBase -> StatisticalMeasures (#194) (@ablaom)
• For a 0.8 release (#195) (@ablaom)
• add compat for julia (#196) (@ablaom)

Closed issues:

• Are GridSearch using the update! method? (#82)
• Improper loss functions silently accepted in training a TunedModel (#184)
• Typo in error message for TunedModel missing arguments (#188)
• Skipping parts of search space? (#189)

v0.7.4

MLJTuning v0.7.4

Diff since v0.7.3

Merged pull requests:

• Tweak a test (#185) (@ablaom)
• Extend compat for MLJBase to include 0.21 (#186) (@ablaom)
• For a 0.7.4 release (#187) (@ablaom)