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This package relies on primitives defined in the JuliaML ecosystem to implement high-performance algorithms for linear models which often produce sparsity in the coefficients.
using Pkg
Pkg.add("SparseRegression")
using SparseRegression
x = randn(10_000, 50)
y = x * range(-1, stop=1, length=50) + randn(10_000)
s = SModel(x, y, L2DistLoss(), L2Penalty())
@time learn!(s)
s