MultiTaskElasticNetRegressor
MultiTaskElasticNetRegressorA model type for constructing a multi-target elastic net regressor, based on MLJScikitLearnInterface.jl, and implementing the MLJ model interface.
From MLJ, the type can be imported using
MultiTaskElasticNetRegressor = @load MultiTaskElasticNetRegressor pkg=MLJScikitLearnInterfaceDo model = MultiTaskElasticNetRegressor() to construct an instance with default hyper-parameters. Provide keyword arguments to override hyper-parameter defaults, as in MultiTaskElasticNetRegressor(alpha=...).
Hyper-parameters
alpha = 1.0l1_ratio = 0.5fit_intercept = truecopy_X = truemax_iter = 1000tol = 0.0001warm_start = falserandom_state = nothingselection = cyclic