API Reference / sklearn / features /

selection.py

scikit-learn selection wrappers.

Generated from the FEATURES_SELECTION table in specs. Registered under sklearn. hub keys, mirroring the native TuiML features/selection family.

Classes

GenericUnivariateSelect

class sklearn.features.selection.GenericUnivariateSelect(_SklearnSelectorMixin, FeatureSelector)

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

Wraps GenericUnivariateSelect. 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.

SelectFdr

class sklearn.features.selection.SelectFdr(_SklearnSelectorMixin, FeatureSelector)

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

Wraps SelectFdr. 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.

SelectFpr

class sklearn.features.selection.SelectFpr(_SklearnSelectorMixin, FeatureSelector)

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

Wraps SelectFpr. 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.

SelectFwe

class sklearn.features.selection.SelectFwe(_SklearnSelectorMixin, FeatureSelector)

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

Wraps SelectFwe. 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.

SelectKBest

class sklearn.features.selection.SelectKBest(_SklearnSelectorMixin, FeatureSelector)

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

Wraps SelectKBest. 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: k, score_func.

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.

SelectPercentile

class sklearn.features.selection.SelectPercentile(_SklearnSelectorMixin, FeatureSelector)

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

Wraps SelectPercentile. 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: percentile, score_func.

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.

VarianceThreshold

class sklearn.features.selection.VarianceThreshold(_SklearnSelectorMixin, FeatureSelector)

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

Wraps VarianceThreshold. 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: threshold.

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.