v0.7.0

• Update to ScientificTypes 0.5.1. This is mainly to improve performance of scitype and coerce in the case of (possibly) missing values and on arrays of Any type. This should speed up the machine constructor in some cases. These changes are mildly breaking but won't effect many users. See these releases notes for details

• Update to MLJBase 0.10.0:

  • Give the partition function a new keyword argument stratify=y for specifying a Finite vector y on which to base stratified partitioning. Query ?partition for details (#113)

  • Add new methods for generating synthetic data sets: make_blobs, make_moons, make_circles, make_regression (#155)

  • Improve show method for the results of performance evaluations (calling evaluate!, evaluate)

  • Add keyword argument repeats=1 to evaluate!/evaluate for repeated resampling. For example, specifying resampling=CV(nfolds=3, shuffle=true), repeats=2 to generate 6 per_fold performance estimates for aggregation. Query ?evaluate! for details (#406)

  • In specifying one-dimensional ranges in tuning, unbounded ranges are now allowed. Query ?range and ?iterator for details.

  • improve show method for MLJType objects that "show as constructed" (#351)

• Update MLJModels to 0.7.0:

  • (new model) Add the AdaBoostStumpClassifier from DecisionTree

  • Arrange for clustering algorithms to predict categorical elements instead of integers (#418)

Under the hood, this release represents some re-organizing of the MLJ stack, with performance evaluation (resampling) and one-dimensional ranges moving to MLJBase.

v0.6.1

• Resolves a bug introduced when using ScientificTypes 0.3.2 (#414 PR #414)

v0.6.0

Update to ScientificTypes 0.3, MLJBase 0.9.1, MLJModels 0.6

v0.5.9

• Re-export table from MLJBase (#381)

• Add learning_curve(model, args...; kwargs...) which is equivalent to learning_curve!(machine(model, args...); kwargs...) (#377, PR #388)

• Resolve minor issues #282, #283.

• Allow learning_curve! to assign a default measure when none specified (#283)

v0.5.8

v0.5.8 (2019-12-05)

Diff since v0.5.7

Merged pull requests:

• Dev (#385) (tlienart)

v0.5.7

v0.5.7 (2019-12-05)

Diff since v0.5.6

Closed issues:

• ArgumentError - scitype mismatch during evaluate (#376)

Merged pull requests:

• Attempt to fix #374 (#383) (tlienart)

v0.5.6

• (Documentation) Add "Learning Curves" section to the manual (#362 PR #372)

• (Bug fix) Fix distributed acceleration in EnsembleModel (#361, PR #370)

• Re-export elscitype from ScientificTypes.jl.

v0.5.5

• (Feature) Enable sample weight support in performance evaluation, in tuning, in ensembling, in @pipelines, in learning networks, and exported composite model types (PR #356)
• (Feature) Update to MLJBase 0.8.4 to enable static transformations depending on user-specified parameters to be included in @pipelines and @from_network exported composite models. Update the "Composing Models" section of the manual accordingly (#291, PR #350)
• (Feature) add stratified sampling (issue #108)

v0.5.4

• (Enhancement) Update to MLJBase 0.8.1 to make available: many new performance measures (do ?measures() to list); confusion_matrix and roc_curve (receiver operator characteristic) methods; methods to list and query available measures, measures(), measures(conditions...) (API same as for querying models with models methods) (PR MLJBase #88)

• (Improvement) Change performance evaluation method evaluate! (for resampling) to aggregate using measure-specific method (as specified by new measure trait aggregation) rather than mean in all cases (PR #333)

v0.5.3

v0.5.3 (2019-11-13)

Diff since v0.5.2

Closed issues:

• Get Started Examples doesn't work on MLJ 0.5.2 (#324)
• Streamline tests (#323)
• Can't use FillImputer with @pipeline ? (#320)
• DecisionTreeClassifier producing strange results after upgrade (#319)
• Move the MLJ manual to new repo MLJManual (#316)
• Example of unpack in ?unpack doesn't work: ERROR: MethodError: no method matching !=(::Symbol) (#313)
• Scitype check after dropping missing values (#306)
• train_test_pairs method in resampling interface needs extra arguments (#297)
• Comments in manual on multivariate targets need updating (#295)
• CV(shuffle=true) does not seem to properly shuffle the data (#289)
• Overload mean, mode and median for Nodes (#288)
• @load is too slow (#280)
• Towards 0.5.2 (#273)
• Create/utilize a style guide (#243)

Merged pull requests:

• Patch release 0.5.3 (#332) (tlienart)