示例#1
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    def get_hyperparameter_search_space(dataset_info=None,
                                        kernel=('poly', 'rbf', 'sigmoid',
                                                'cosine'),
                                        n_components=(10, 2000),
                                        gamma=((3.0517578125e-05, 8), True),
                                        degree=(2, 5),
                                        coef0=(-1, 1)):
        cs = ConfigSpace.ConfigurationSpace()
        kernel_hp = add_hyperparameter(cs, CSH.CategoricalHyperparameter,
                                       'kernel', kernel)
        add_hyperparameter(cs, CSH.UniformIntegerHyperparameter,
                           "n_components", n_components)

        if "poly" in kernel:
            degree_hp = add_hyperparameter(cs,
                                           CSH.UniformIntegerHyperparameter,
                                           'degree', degree)
            cs.add_condition(CSC.EqualsCondition(degree_hp, kernel_hp, "poly"))
        if set(["poly", "sigmoid"]) & set(kernel):
            coef0_hp = add_hyperparameter(cs, CSH.UniformFloatHyperparameter,
                                          "coef0", coef0)
            cs.add_condition(
                CSC.InCondition(coef0_hp, kernel_hp,
                                list(set(["poly", "sigmoid"]) & set(kernel))))
        if set(["poly", "rbf", "sigmoid"]) & set(kernel):
            gamma_hp = add_hyperparameter(cs, CSH.UniformFloatHyperparameter,
                                          "gamma", gamma)
            cs.add_condition(
                CSC.InCondition(
                    gamma_hp, kernel_hp,
                    list(set(["poly", "rbf", "sigmoid"]) & set(kernel))))
        return cs
示例#2
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    def get_hyperparameter_search_space():

        possible_kernels = ['poly', 'rbf', 'sigmoid', 'cosine']
        kernel = CSH.CategoricalHyperparameter('kernel', possible_kernels,
                                               'rbf')
        n_components = CSH.UniformIntegerHyperparameter("n_components",
                                                        50,
                                                        10000,
                                                        default_value=100,
                                                        log=True)
        gamma = CSH.UniformFloatHyperparameter("gamma",
                                               3.0517578125e-05,
                                               8,
                                               log=True,
                                               default_value=0.1)
        degree = CSH.UniformIntegerHyperparameter('degree', 2, 5, 3)
        coef0 = CSH.UniformFloatHyperparameter("coef0", -1, 1, default_value=0)

        cs = ConfigSpace.ConfigurationSpace()
        cs.add_hyperparameters([kernel, degree, gamma, coef0, n_components])

        degree_depends_on_poly = CSC.EqualsCondition(degree, kernel, "poly")
        coef0_condition = CSC.InCondition(coef0, kernel, ["poly", "sigmoid"])

        gamma_kernels = ["poly", "rbf", "sigmoid"]
        gamma_condition = CSC.InCondition(gamma, kernel, gamma_kernels)
        cs.add_conditions(
            [degree_depends_on_poly, coef0_condition, gamma_condition])
        return cs
示例#3
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    def get_hyperparameter_search_space(dataset_properties=None):
        cs = ConfigSpace.ConfigurationSpace()

        n_components = CSH.UniformIntegerHyperparameter("n_components", lower=10, upper=2000)
        algorithm = CSH.CategoricalHyperparameter('algorithm', ['parallel', 'deflation'])
        whiten = CSH.CategoricalHyperparameter('whiten', [True, False])
        fun = CSH.CategoricalHyperparameter('fun', ['logcosh', 'exp', 'cube'])
        cs.add_hyperparameters([n_components, algorithm, whiten, fun])

        cs.add_condition(CSC.EqualsCondition(n_components, whiten, True))

        return cs
示例#4
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    def get_hyperparameter_search_space(dataset_properties=None):
        n_components = CSH.UniformIntegerHyperparameter("n_components",
                                                        10,
                                                        2000,
                                                        default_value=100)
        kernel = CSH.CategoricalHyperparameter(
            'kernel', ['poly', 'rbf', 'sigmoid', 'cosine'], 'rbf')
        gamma = CSH.UniformFloatHyperparameter("gamma",
                                               3.0517578125e-05,
                                               8,
                                               log=True,
                                               default_value=1.0)
        degree = CSH.UniformIntegerHyperparameter('degree', 2, 5, 3)
        coef0 = CSH.UniformFloatHyperparameter("coef0", -1, 1, default_value=0)
        cs = ConfigSpace.ConfigurationSpace()
        cs.add_hyperparameters([n_components, kernel, degree, gamma, coef0])

        degree_depends_on_poly = CSC.EqualsCondition(degree, kernel, "poly")
        coef0_condition = CSC.InCondition(coef0, kernel, ["poly", "sigmoid"])
        gamma_condition = CSC.InCondition(gamma, kernel, ["poly", "rbf"])
        cs.add_conditions(
            [degree_depends_on_poly, coef0_condition, gamma_condition])
        return cs
示例#5
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    def get_hyperparameter_search_space(
            dataset_info=None,
            n_components=(10, 2000),
            algorithm=('parallel', 'deflation'),
            whiten=(True, False),
            fun=('logcosh', 'exp', 'cube'),
    ):
        cs = ConfigSpace.ConfigurationSpace()

        n_components_hp = get_hyperparameter(CSH.UniformIntegerHyperparameter,
                                             "n_components", n_components)
        algorithm_hp = get_hyperparameter(CSH.CategoricalHyperparameter,
                                          'algorithm', algorithm)
        whiten_hp = get_hyperparameter(CSH.CategoricalHyperparameter, 'whiten',
                                       whiten)
        fun_hp = get_hyperparameter(CSH.CategoricalHyperparameter, 'fun', fun)

        if True in whiten:
            cs.add_hyperparameters(
                [n_components_hp, algorithm_hp, whiten_hp, fun_hp])
            cs.add_condition(
                CSC.EqualsCondition(n_components_hp, whiten_hp, True))

        return cs