8565a366de87d82dc19c3386b4a83359be1aa275,autosklearn/pipeline/components/classification/decision_tree.py,DecisionTree,get_hyperparameter_search_space,#Any#,84

Before Change

    def get_hyperparameter_search_space(dataset_properties=None):
        cs = ConfigurationSpace()

        criterion = cs.add_hyperparameter(CategoricalHyperparameter(
            "criterion", ["gini", "entropy"], default="gini"))
        splitter = cs.add_hyperparameter(Constant("splitter", "best"))
        max_features = cs.add_hyperparameter(Constant("max_features", 1.0))
        max_depth = cs.add_hyperparameter(UniformFloatHyperparameter(
            "max_depth", 0., 2., default=0.5))
        min_samples_split = cs.add_hyperparameter(UniformIntegerHyperparameter(
            "min_samples_split", 2, 20, default=2))
        min_samples_leaf = cs.add_hyperparameter(UniformIntegerHyperparameter(
            "min_samples_leaf", 1, 20, default=1))
        min_weight_fraction_leaf = cs.add_hyperparameter(
            Constant("min_weight_fraction_leaf", 0.0))
        max_leaf_nodes = cs.add_hyperparameter(
            UnParametrizedHyperparameter("max_leaf_nodes", "None"))

        return cs

After Change

    @staticmethod
    def get_hyperparameter_search_space(dataset_properties=None):
        cs = ConfigurationSpace()

        criterion = CategoricalHyperparameter(
            "criterion", ["gini", "entropy"], default="gini")
        splitter = Constant("splitter", "best")
        max_features = Constant("max_features", 1.0)
        max_depth = UniformFloatHyperparameter(
            "max_depth", 0., 2., default=0.5)
        min_samples_split = UniformIntegerHyperparameter(
            "min_samples_split", 2, 20, default=2)
        min_samples_leaf = UniformIntegerHyperparameter(
            "min_samples_leaf", 1, 20, default=1)
        min_weight_fraction_leaf = Constant("min_weight_fraction_leaf", 0.0)
        max_leaf_nodes = UnParametrizedHyperparameter("max_leaf_nodes", "None")

        cs.add_hyperparameters([criterion, splitter, max_features, max_depth,
                                min_samples_split, min_samples_leaf,
                                min_weight_fraction_leaf, max_leaf_nodes])

        return cs

Instances