API Reference / sklearn /

clustering.py

scikit-learn clustering wrappers.

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

Classes

AffinityPropagation

class sklearn.clustering.AffinityPropagation(_SklearnClustererMixin, Clusterer)

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

Wraps AffinityPropagation. 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.

AgglomerativeClustering

class sklearn.clustering.AgglomerativeClustering(_SklearnClustererMixin, Clusterer)

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

Wraps AgglomerativeClustering. 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: n_clusters, linkage, metric.

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.

BayesianGaussianMixture

class sklearn.clustering.BayesianGaussianMixture(_SklearnClustererMixin, Clusterer)

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

Wraps BayesianGaussianMixture. 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.

Birch

class sklearn.clustering.Birch(_SklearnClustererMixin, Clusterer)

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

Wraps Birch. 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.

BisectingKMeans

class sklearn.clustering.BisectingKMeans(_SklearnClustererMixin, Clusterer)

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

Wraps BisectingKMeans. 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.

DBSCAN

class sklearn.clustering.DBSCAN(_SklearnClustererMixin, Clusterer)

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

Wraps DBSCAN. 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: eps, min_samples, metric.

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.

GaussianMixture

class sklearn.clustering.GaussianMixture(_SklearnClustererMixin, Clusterer)

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

Wraps GaussianMixture. 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: n_components, covariance_type, random_state.

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.

HDBSCAN

class sklearn.clustering.HDBSCAN(_SklearnClustererMixin, Clusterer)

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

Wraps HDBSCAN. 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.

KMeans

class sklearn.clustering.KMeans(_SklearnClustererMixin, Clusterer)

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

Wraps KMeans. 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: n_clusters, init, n_init, random_state.

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.

MeanShift

class sklearn.clustering.MeanShift(_SklearnClustererMixin, Clusterer)

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

Wraps MeanShift. 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.

MiniBatchKMeans

class sklearn.clustering.MiniBatchKMeans(_SklearnClustererMixin, Clusterer)

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

Wraps MiniBatchKMeans. 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.

OPTICS

class sklearn.clustering.OPTICS(_SklearnClustererMixin, Clusterer)

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

Wraps OPTICS. 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.

SpectralClustering

class sklearn.clustering.SpectralClustering(_SklearnClustererMixin, Clusterer)

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

Wraps SpectralClustering. 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.