MLJ News

Development news for MLJ and its satellite packages, MLJBase, MLJRegistry and MLJModels

unversioned commits 12 April 2019 (around 00:10, GMT)

• Added out-of-bag estimates for performance in homogeneous ensembles. Resolves: #77

unversioned commits 11 April 2019 (before noon, GMT)

• Removed dependency on unregistered package TOML.jl (using, Pkg.TOML instead). Resolves #113

unversioned commits 8 April 2019 (some time after 20:00 GMT)

• Addition of XGBoost models XGBoostRegressor, XGBoostClassifier and XGBoostCount. Resolves #65.

• Documentation reorganized as GitHub pages. Includes some additions but still a work in progress.

unversioned commits 1 March 2019 (some time after 03:50 GMT)

• Addition of "scientific type" hierarchy, including Continuous, Discrete, Multiclass, and Other subtypes of Found (to complement Missing). See Getting Started for more one this. Resolves: #86

• Revamp of model traits to take advantage of scientific types, with output_kind replaced with target_scitype_union, input_kind replaced with input_scitype. Also, output_quantity dropped, input_quantity replaced with Bool-valued input_is_multivariate, and is_pure_julia made Bool-valued. Trait definitions in all model implementations and effected meta-algorithms have been updated. Related: #81

• Substantial update of the core guide Adding New Models to reflect above changes and in response to new model implementer queries. Some design "decisions" regarding multivariate targets now explict there.

• the order the y and yhat arguments of measures (aka loss functions) have been reversed. Progress on: #91

• Update of Standardizer and OneHotEncoder to mesh with new scitypes.

• New improved task constructors infer task metadata from data scitypes. This brings us close to a simple implementation of basic task-model matching. Query the doc-strings for SupervisedTask and UnsupervisedTask for details. Machines can now dispatch on tasks instead of X and y. A task, task, is now callable: task() returns (X, y) for supervised models, and X for unsupervised models. Progress on: #86

• the data in the load_ames() test task has been replaced by the full data set, and load_reduced_ames() now loads a reduced set.