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))It is possible train a learning model (e.g. RandomForestClassifier) with
the train table to approximate a :target label and perform predictions
with the test table:
model = RandomForestClassifier()
learn = Learn(label(train, :target); model)
preds = learn(test)The function label is used to tag columns of the table with target labels,
which can be categorical or continuous. Remaining columns are assumed to be
predictors.
Please check the models directory for documentation on available models and their parameters.