PassiveAggressiveRegressor

PassiveAggressiveRegressor

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

From MLJ, the type can be imported using

PassiveAggressiveRegressor = @load PassiveAggressiveRegressor pkg=MLJScikitLearnInterface

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

Hyper-parameters

• C = 1.0
• fit_intercept = true
• max_iter = 1000
• tol = 0.0001
• early_stopping = false
• validation_fraction = 0.1
• n_iter_no_change = 5
• shuffle = true
• verbose = 0
• loss = epsilon_insensitive
• epsilon = 0.1
• random_state = nothing
• warm_start = false
• average = false