API Reference / sklearn /

svm.py

scikit-learn svm wrappers.

Generated from the SVM table in specs. Registered under sklearn. hub keys, mirroring the native TuiML svm family.

Classes

LinearSVC

class sklearn.svm.LinearSVC(_SklearnBackedMixin, Classifier)

scikit-learn LinearSVC (hub key sklearn.LinearSVC).

Wraps LinearSVC. Accepts that estimator's constructor parameters as keyword arguments; call get_parameter_schema for the full list with types and defaults derived from the installed scikit-learn.

Commonly set: C, loss, max_iter.

Constructor 
__init__(
    self,
    **params,
)

Methods

__init__ (self, **params)
get_parameter_schema (cls) -> Dict[str, Any]

Return JSON Schema for constructor parameters.

get_capabilities (cls) -> List[str]

Return the capability names this wrapper supports.

NuSVC

class sklearn.svm.NuSVC(_SklearnBackedMixin, Classifier)

scikit-learn NuSVC (hub key sklearn.NuSVC).

Wraps NuSVC. Accepts that estimator's constructor parameters as keyword arguments; call get_parameter_schema for the full list with types and defaults derived from the installed scikit-learn.
Constructor 
__init__(
    self,
    **params,
)

Methods

__init__ (self, **params)
get_parameter_schema (cls) -> Dict[str, Any]

Return JSON Schema for constructor parameters.

get_capabilities (cls) -> List[str]

Return the capability names this wrapper supports.

SVC

class sklearn.svm.SVC(_SklearnBackedMixin, Classifier)

scikit-learn SVC (hub key sklearn.SVC).

Wraps SVC. Accepts that estimator's constructor parameters as keyword arguments; call get_parameter_schema for the full list with types and defaults derived from the installed scikit-learn.

Commonly set: C, kernel, gamma, probability.

Constructor 
__init__(
    self,
    **params,
)

Methods

__init__ (self, **params)
get_parameter_schema (cls) -> Dict[str, Any]

Return JSON Schema for constructor parameters.

get_capabilities (cls) -> List[str]

Return the capability names this wrapper supports.

LinearSVR

class sklearn.svm.LinearSVR(_SklearnBackedMixin, Regressor)

scikit-learn LinearSVR (hub key sklearn.LinearSVR).

Wraps LinearSVR. Accepts that estimator's constructor parameters as keyword arguments; call get_parameter_schema for the full list with types and defaults derived from the installed scikit-learn.
Constructor 
__init__(
    self,
    **params,
)

Methods

__init__ (self, **params)
get_parameter_schema (cls) -> Dict[str, Any]

Return JSON Schema for constructor parameters.

get_capabilities (cls) -> List[str]

Return the capability names this wrapper supports.

NuSVR

class sklearn.svm.NuSVR(_SklearnBackedMixin, Regressor)

scikit-learn NuSVR (hub key sklearn.NuSVR).

Wraps NuSVR. Accepts that estimator's constructor parameters as keyword arguments; call get_parameter_schema for the full list with types and defaults derived from the installed scikit-learn.
Constructor 
__init__(
    self,
    **params,
)

Methods

__init__ (self, **params)
get_parameter_schema (cls) -> Dict[str, Any]

Return JSON Schema for constructor parameters.

get_capabilities (cls) -> List[str]

Return the capability names this wrapper supports.

SVR

class sklearn.svm.SVR(_SklearnBackedMixin, Regressor)

scikit-learn SVR (hub key sklearn.SVR).

Wraps SVR. Accepts that estimator's constructor parameters as keyword arguments; call get_parameter_schema for the full list with types and defaults derived from the installed scikit-learn.

Commonly set: C, kernel, epsilon.

Constructor 
__init__(
    self,
    **params,
)

Methods

__init__ (self, **params)
get_parameter_schema (cls) -> Dict[str, Any]

Return JSON Schema for constructor parameters.

get_capabilities (cls) -> List[str]

Return the capability names this wrapper supports.