logml.models.registry.svm

Classes

BaseSVMModel([params, logger])	Base class for sklearn.svm* models.
LinearSVCClassifierModel([params, logger])	Wrapper for sklearn.svm.LinearSVC.
SVCClassifierModel([params, logger])	Wrapper for sklearn.svm.SVC.
SVRClassifierModel([params, logger])	Wrapper for sklearn.svm.SVR.

class logml.models.registry.svm.BaseSVMModel(params: Optional[dict] = None, logger=None)

Bases: logml.models.base.BaseModel

Base class for sklearn.svm* models.

TAGS = ['svm', 'no_predict_proba']

FE_MODEL_ATTRIBUTE = None

class logml.models.registry.svm.LinearSVCClassifierModel(params: Optional[dict] = None, logger=None)

Bases: logml.models.registry.svm.BaseSVMModel

Wrapper for sklearn.svm.LinearSVC.

TASK = 'classification'

FE_MODEL_ATTRIBUTE = 'coef_'

F_MODEL

alias of sklearn.svm._classes.LinearSVC

DEFAULT_PARAMS = {'random_state': None}

PARAMS_SPACE = {'C': [0.01, 0.1, 1], 'dual': [True, False], 'fit_intercept': [True, False], 'penalty': ['l1', 'l2']}

class logml.models.registry.svm.SVCClassifierModel(params: Optional[dict] = None, logger=None)

Bases: logml.models.registry.svm.BaseSVMModel

Wrapper for sklearn.svm.SVC.

TASK = 'classification'

F_MODEL

alias of sklearn.svm._classes.SVC

DEFAULT_PARAMS = {'probability': True, 'random_state': None}

PARAMS_SPACE = {'C': {'distribution': 'loguniform', 'params': [-5, 15]}, 'cache_size': [200], 'degree': [2, 3, 4], 'gamma': {'distribution': 'loguniform', 'params': [-15, 3]}, 'kernel': ['poly', 'rbf', 'sigmoid'], 'probability': [True], 'random_state': [None], 'tol': [0.001]}

class logml.models.registry.svm.SVRClassifierModel(params: Optional[dict] = None, logger=None)

Bases: logml.models.registry.svm.BaseSVMModel

Wrapper for sklearn.svm.SVR.

TASK = 'regression'

F_MODEL

alias of sklearn.svm._classes.SVR

DEFAULT_PARAMS = {'degree': 2}

PARAMS_SPACE = {'C': {'distribution': 'loguniform', 'params': [-12, 2]}, 'degree': [1, 2, 3, 4], 'epsilon': {'distribution': 'loguniform', 'params': [-12, 2]}, 'kernel': ['linear', 'poly', 'rbf', 'sigmoid']}