code snippet for Tuning Hyperparameters (part I): SuccessiveHalving

SHSklearnEstimato_illustration

class SHSklearnEstimator(SHBaseEstimator):
    def __init__(self,model,ressource_name=None):
        self.model = model
        self.ressource_name = ressource_name
        self.env = None

    def update(self,Xtrain,ytrain,Xval,yval,scoring,n_iterations):
        self.set_params(**{'warm_start':True,self.ressource_name:n_iterations})
        self.model.fit(Xtrain,ytrain)