{"allOf": [
        {   "type": "object",
            "additionalProperties": "False",
            "required": ["kernel", "degree", "gamma", "shrinking", "tol", "cache_size", "max_iter", "decision_function_shape"],
            "relevantToOptimizer": ["kernel", "degree", "gamma", "shrinking", "probability", "tol"],
            "properties": {
                "C": {
                    "description": "Penalty parameter C of the error term.",
                    "type": "number",
                    "distribution": "loguniform",
                    "minimum": 0.0,
                    "exclusiveMinimum": "True",
                    "default": 1.0,
                    "minimumForOptimizer": 0.03125,
                    "maximumForOptimizer": 32768},
                "kernel": {
                    "anyOf": [
                        {   "enum":["precomputed"], "forOptimizer": "False"},
                        {   "enum": ["linear", "poly", "rbf", "sigmoid"]},
                        {   "laleType": "callable", "forOptimizer": "False"}],
                    "default": "rbf",
                    "description":
                    "Specifies the kernel type to be used in the algorithm."},
                "degree": {
                    "type": "integer",
                    "minimum": 0,
                    "minimumForOptimizer": 2,
                    "maximumForOptimizer": 5,
                    "default": 3,
                    "description": "Degree of the polynomial kernel function ('poly')."},
                "gamma": {
                    "anyOf": [
                        {   "type": "number",
                            "minimum": 0.0,
                            "exclusiveMinimum": "True",
                            "minimumForOptimizer": 3.0517578125e-05,
                            "maximumForOptimizer": 8,
                            "distribution": "loguniform"},
                        {   "enum": ["auto", "auto_deprecated", "scale"]}],
                    "default": "auto_deprecated",
                    "description": "Kernel coefficient for 'rbf', 'poly', and 'sigmoid'."},
                "coef0": {
                    "type": "number",
                    "default": 0.0,
                    "description": "Independent term in kernel function."},
                "shrinking": {
                    "type": "boolean",
                    "default": "True",
                    "description": "Whether to use the shrinking heuristic."},
                "probability": {
                    "type": "boolean",
                    "default": "False",
                    "description": "Whether to enable probability estimates."},
                "tol": {
                    "type": "number",
                    "distribution": "loguniform",
                    "minimum": 0.0,
                    "exclusiveMinimum": "True",
                    "maximumForOptimizer": 0.01,
                    "default": 0.0001,
                    "description": "Tolerance for stopping criteria."},
                "cache_size": {
                    "type": "integer",
                    "default": 200,
                    "description": "Specify the size of the kernel cache (in MB)."},
                "class_weight": {
                    "anyOf": [
                        { "description": "By default, all classes have weight 1.",
                            "enum": [null]},
                        { "description": "Adjust weights by inverse frequency.",
                            "enum": ["balanced"]},
                        { "description": "Dictionary mapping class labels to weights.",
                            "type": "object",
                            "additionalProperties": {"type": "number"},
                            "forOptimizer": "False"}],
                    "default": null},
                "verbose": {
                    "type": "boolean",
                    "default": "False",
                    "description": "Enable verbose output."},
                "max_iter": {
                    "type": "integer",
                    "default": -1,
                    "description": "Hard limit on iterations within solver, or -1 for no limit."},
                "decision_function_shape": {
                    "enum": ["ovo", "ovr"],
                    "default": "ovr",
                    "description": "Whether to return a one-vs-rest ('ovr') decision function of shape (n_samples, n_classes) as all other classifiers, or the original one-vs-one (‘ovo’) decision function of libsvm which has shape (n_samples, n_classes * (n_classes - 1) / 2)."},
                "random_state": {
                    "description":
                    "Seed of pseudo-random number generator.",
                    "anyOf": [
                        {   "laleType": "numpy.random.RandomState"},
                        {   "description": "RandomState used by np.random",
                            "enum": [null]},
                        {   "description": "Explicit seed.",
                            "type": "integer"}],
                    "default": null}}},
        {   "description": "coef0 only significant in kernel ‘poly’ and ‘sigmoid’.",
            "anyOf": [
                {   "type": "object",
                    "properties": {"kernel": {"enum": ["poly", "sigmoid"]}}},
                {   "type": "object",
                    "properties": {"coef0": {"enum": [0.0]}}}]}]}