ElasticNetRegressor

ElasticNetRegressor

A model type for constructing a elastic net regressor, based on MLJScikitLearnInterface.jl, and implementing the MLJ model interface.

From MLJ, the type can be imported using

ElasticNetRegressor = @load ElasticNetRegressor pkg=MLJScikitLearnInterface

Do model = ElasticNetRegressor() to construct an instance with default hyper-parameters. Provide keyword arguments to override hyper-parameter defaults, as in ElasticNetRegressor(alpha=...).

Hyper-parameters

• alpha = 1.0
• l1_ratio = 0.5
• fit_intercept = true
• precompute = false
• max_iter = 1000
• copy_X = true
• tol = 0.0001
• warm_start = false
• positive = false
• random_state = nothing
• selection = cyclic