A place for non-native implementations of the MLJ model API
Repository of the “built-in” models available for use in the
MLJ MLJ machine
learning framework; and the home of the MLJ model registry.
For instructions on integrating a new model with MLJ visit
here
General users of the MLJ machine learning platform should refer to
MLJ home page
for usage and installation instructions. MLJModels is a dependency of
MLJ that the general user can ignore.
This repository is for developers wishing to
register new MLJ
model interfaces, whether they be:
implemented natively in a
package providing the core machine learning algorithm, as inEvoTrees.jl
; or
implemented in a separate interface package, such as
MLJDecisionTreeInterface.jl.
It also a place for developers to add models (mostly transformers)
such as OneHotEncoder
, that are exported for “built-in” use in
MLJ. (In the future these models may live in a separate package.)
To list all model interfaces currently registered, do using MLJ
orusing MLJModels
and run:
localmodels()
to list built-in models (updated when external models are loaded with @load
)
models()
to list all registered models, or see this list.
Recall that an interface is loaded from within MLJ, together with the
package providing the underlying algorithm, using the syntax @load
RidgeRegressor pkg=GLM
, where the pkg
keyword is only necessary in
ambiguous cases.
MLJModels contains:
transformers to be pre-loaded into MLJ, located at
/src/builtins, such as OneHotEncoder
and ConstantClassifier
.
the MLJ model registry, listing all
models that can be called from MLJ using @load
. Package developers
can register new models by implementing the MLJ interface in their
package and following these
instructions.
Generally model registration is performed by administrators. If you
have an interface you would like registered, open an issue
here.
Administrator instructions. These are given in theMLJModels.@update
document string. After registering the model, make a PR to MLJ
updating this dictionary of model descriptors
to ensure the new models appear in the right places in MLJ’s Model Browser