`tlc.client.reduce.umap`#

Dimensionality reduction with the UMAP algorithm.

Module Contents#

Class	Description
`UMapTableArgs`	Arguments specific to the UMAP reduction method.
`UMapReduction`	Perform dimensionality reduction on columns of tables using the UMAP algorithm.

class tlc.client.reduce.umap.UMapTableArgs#

Bases: tlc.client.reduce.reduction_method.ReducerArgs

Arguments specific to the UMAP reduction method.

See UMAPTable for more information.

Initialize self. See help(type(self)) for accurate signature.

n_components: int = None#: The number of dimensions in the reduced space (default 2).

standard_scaler_normalize: bool = None#: Whether to normalize the data before reducing it (default False).

n_neighbors: int = None#: The number of neighbors to use when constructing the nearest neighbor graph (default 15).

metric: str = None#: The metric to use when calculating distances between points in the input space (default: euclidean).

min_dist: float = None#: The minimum distance between points in the reduced space (default 0.1).

n_jobs: int = None#: The number of threads to use for the reduction (default -1).

class tlc.client.reduce.umap.UMapReduction(reducer_args: tlc.client.reduce.reduction_method._ReducerArgsType | None = None)#

Perform dimensionality reduction on columns of tables using the UMAP algorithm.

Params reducer_args:: A dictionary of arguments which are specific to the reduction method.

default_args() → tlc.client.reduce.umap.UMapTableArgs#: Returns the default arguments for the UMAP reduction method.

fit_reduction_method(table: tlc.core.objects.table.Table, column: str) → tlc.core.url.Url#: Fits a UMAPTable and returns the model URL

apply_reduction_method(table: tlc.core.objects.table.Table, fit_table_url: tlc.core.url.Url, column: str) → tlc.core.url.Url | None#