deepaugment/controller.py
def init_skopt(self, opt_initial_points):
        """Initialize as scikit-optimize (skopt) Optimizer with a 5-dimensional search space

        Aligned with skopt ask-tell design pattern (https://geekyisawesome.blogspot.com/2018/07/hyperparameter-tuning-using-scikit.html)

        Args:
            opt_initial_points (int): number of random initial points for the optimizer
        """

        self.opt = skopt.Optimizer(
            [
                skopt.space.Categorical(AUG_TYPES, name="A_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="A_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="A_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="A_aug2_magnitude"),

                skopt.space.Categorical(AUG_TYPES, name="B_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="B_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="B_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="B_aug2_magnitude"),

                skopt.space.Categorical(AUG_TYPES, name="C_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="C_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="C_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="C_aug2_magnitude"),

                skopt.space.Categorical(AUG_TYPES, name="D_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="D_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="D_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="D_aug2_magnitude"),

                skopt.space.Categorical(AUG_TYPES, name="E_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="E_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="E_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="E_aug2_magnitude")
            ],
            n_initial_points=opt_initial_points,
            base_estimator="RF",  # Random Forest estimator
            acq_func="EI",  # Expected Improvement
            acq_optimizer="auto",
            random_state=0,
        )
Initialize as scikit-optimize (skopt) Optimizer with a 5-dimensional search space

        Aligned with skopt ask-tell design pattern (https://geekyisawesome.blogspot.com/2018/07/hyperparameter-tuning-using-scikit.html)

        Args:
            opt_initial_points (int): number of random initial points for the optimizer
        
Initialize as scikit-optimize (skopt) Optimizer with a 5-dimensional search space
Aligned with skopt ask-tell design pattern
Initialize as scikit - optimize ( skopt ) Optimizer with a 5 - dimensional search space Aligned with skopt ask - tell design pattern
def init_skopt(self, opt_initial_points):
        self.opt = skopt.Optimizer(
            [
                skopt.space.Categorical(AUG_TYPES, name="A_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="A_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="A_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="A_aug2_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="B_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="B_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="B_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="B_aug2_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="C_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="C_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="C_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="C_aug2_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="D_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="D_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="D_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="D_aug2_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="E_aug1_type"),
                skopt.space.Real(0.0, 1.0, name="E_aug1_magnitude"),
                skopt.space.Categorical(AUG_TYPES, name="E_aug2_type"),
                skopt.space.Real(0.0, 1.0, name="E_aug2_magnitude")
            ],
            n_initial_points=opt_initial_points,
            base_estimator="RF",  
            acq_func="EI",  
            acq_optimizer="auto",
            random_state=0,
        )
def init_skopt ( self , opt_initial_points ) : self . opt = skopt . Optimizer ( [ skopt . space . Categorical ( AUG_TYPES , name = "A_aug1_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "A_aug1_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "A_aug2_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "A_aug2_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "B_aug1_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "B_aug1_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "B_aug2_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "B_aug2_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "C_aug1_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "C_aug1_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "C_aug2_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "C_aug2_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "D_aug1_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "D_aug1_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "D_aug2_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "D_aug2_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "E_aug1_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "E_aug1_magnitude" ) , skopt . space . Categorical ( AUG_TYPES , name = "E_aug2_type" ) , skopt . space . Real ( 0.0 , 1.0 , name = "E_aug2_magnitude" ) ] , n_initial_points = opt_initial_points , base_estimator = "RF" , acq_func = "EI" , acq_optimizer = "auto" , random_state = 0 , )
Initialize as scikit-optimize (skopt) Optimizer with a 5-dimensional search space
Aligned with skopt ask-tell design pattern (https://geekyisawesome.blogspot.com/2018/07/hyperparameter-tuning-using-scikit.html)
Initialize as scikit - optimize ( skopt ) Optimizer with a 5 - dimensional search space Aligned with skopt ask - tell design pattern ( https : // geekyisawesome . blogspot . com / 2018 / 07 / hyperparameter - tuning - using - scikit . html )
"""Initialize as scikit-optimize (skopt) Optimizer with a 5-dimensional search space

        Aligned with skopt ask-tell design pattern (https://geekyisawesome.blogspot.com/2018/07/hyperparameter-tuning-using-scikit.html)

        Args:
            opt_initial_points (int): number of random initial points for the optimizer
        """ # Random Forest estimator # Expected Improvement
self
opt_initial_points
number of random initial points for the optimizer
number of random initial points for the optimizer