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