This is a Julia implementation of the maxnet algorithm, with all core functionality in the original R package.
Maxnet transforms input data in various ways and then uses the GLMnet algorithm to fit a lasso path, selecting the best variables and transformations.
Maxnet is closely related to the Java MaxEnt application, which is widely used in species distribution modelling. Maxnet was introduced in this publication, which goes more into details about the algorithm.
Also see the Maxent page on the site of the American Museum for Natural History.
A basic example, using a toy dataset included in the package:
using Maxnet
p_a, env = Maxnet.bradypus()
bradypus_model = maxnet(p_a, env)
prediction = predict(bradypus_model, env)Maxnet integrates with MLJ through the MaxnetBinaryClassifier type.