Statistical learning models for Tables.jl tables.
Get the latest stable release with Julia's package manager:
] add StatsLearnModels
This package provides a Learn transform that implements the
TableTransforms.jl
interface.
Given two Tables.jl tables with training and test data:
train = (feature1=rand(100), feature2=rand(100), target=rand(1:2, 100))
test = (feature1=rand(20), feature2=rand(20))One can train a learning model (e.g. RandomForestClassifier) with
the train table:
model = RandomForestClassifier()
learn = Learn(train, model, ["feature1","feature2"] => "target")and apply the trained model to the test table:
pred = learn(test)The package exports native Julia models from various packages in the ecosystem. It is also possible to use models from the MLJ.jl stack.
The combination of TableTransforms.jl with StatsLearnModels.jl can be thought of as a powerful alternative to MLJ.jl.