actableai.embedding.models package

Subpackages

• actableai.embedding.models.tests package
  • Submodules
  • actableai.embedding.models.tests.test_models module
  • Module contents

Submodules

actableai.embedding.models.base module

class actableai.embedding.models.base.BaseEmbeddingModel(embedding_size: int = 2, parameters: Optional[Dict[str, Any]] = None, process_parameters: bool = True, verbosity: int = 1)

Bases: actableai.models.base.AAIParametersModel[numpy.ndarray, numpy.ndarray], abc.ABC

has_fit: bool = True

has_transform: bool = True

class actableai.embedding.models.base.EmbeddingModelWrapper(embedding_size: int = 2, parameters: Optional[Dict[str, Any]] = None, process_parameters: bool = True, verbosity: int = 1)

Bases: actableai.embedding.models.base.BaseEmbeddingModel, abc.ABC

initialize_model()

class actableai.embedding.models.base.Model(value)

Bases: str, enum.Enum

Enum representing the different model available.

linear_discriminant_analysis = 'linear_discriminant_analysis'

tsne = 'tsne'

umap = 'umap'

actableai.embedding.models.linear_discriminant_analysis module

class actableai.embedding.models.linear_discriminant_analysis.LinearDiscriminantAnalysis(embedding_size: int = 2, parameters: Optional[Dict[str, Any]] = None, process_parameters: bool = True, verbosity: int = 1)

Bases: actableai.embedding.models.base.EmbeddingModelWrapper

Class to handle LDA.

static get_parameters() → actableai.parameters.parameters.Parameters

Returns the parameters of the model.

Returns

The parameters.

actableai.embedding.models.tsne module

class actableai.embedding.models.tsne.TSNE(embedding_size: int = 2, parameters: Optional[Dict[str, Any]] = None, process_parameters: bool = True, verbosity: int = 1)

Bases: actableai.embedding.models.base.EmbeddingModelWrapper

Class to handle TSNE.

static get_parameters() → actableai.parameters.parameters.Parameters

Returns the parameters of the model.

Returns

The parameters.

actableai.embedding.models.umap module

class actableai.embedding.models.umap.UMAP(embedding_size: int = 2, parameters: Optional[Dict[str, Any]] = None, process_parameters: bool = True, verbosity: int = 1)

Bases: actableai.embedding.models.base.EmbeddingModelWrapper

Class to handle UMAP.

static get_parameters() → actableai.parameters.parameters.Parameters

Returns the parameters of the model.

Returns

The parameters.

Module contents