## MLJTuning v0.8.8

[Diff since v0.8.7](v0.8.7...v0.8.8)

- 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)

## MLJTuning v0.8.7

[Diff since v0.8.6](v0.8.6...v0.8.7)


**Merged pull requests:**
- Overload `constructor` trait for `TunedModel` types (#219) (@ablaom)
- For a 0.8.7 release (#220) (@ablaom)

## MLJTuning v0.8.6

[Diff since v0.8.5](v0.8.5...v0.8.6)

- (**new feature**) Add `logger` option to `TunedModel` wrapper, for logging internal model evaluations to an ML tracking platform,  such as MLflow via [MLJFlow.jl](https://github.com/JuliaAI/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()`. Currently, `CPU1()` (the default) is supported by MLJFlow.jl's loggers, while ansynchronous support is a work in progress; see JuliaAI/MLJFlow.jl#41 #193.

**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)

## MLJTuning v0.8.5

[Diff since v0.8.4](v0.8.4...v0.8.5)

- 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)

## MLJTuning v0.8.4

[Diff since v0.8.3](v0.8.3...v0.8.4)

- (**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)

## MLJTuning v0.8.3

[Diff since v0.8.2](v0.8.2...v0.8.3)

- 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)

## MLJTuning v0.8.2

[Diff since v0.8.1](v0.8.1...v0.8.2)


**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)

## MLJTuning v0.8.1

[Diff since v0.8.0](v0.8.0...v0.8.1)


**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)

## MLJTuning v0.8.0

[Diff since v0.7.4](v0.7.4...v0.8.0)

- (**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](https://github.com/alan-turing-institute/MLJ.jl/blob/measure/docs/src/performance_measures.md#migration-guide-for-changes-to-measures-in-mljbase-10) (#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)

## MLJTuning v0.7.4

[Diff since v0.7.3](v0.7.3...v0.7.4)



**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)