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