tlc.core.objects.tables.from_table.pacmap_table¶

A Table where a column from the input Table has been dimensionally reduced by the PaCMAP algorithm.

Module Contents¶

Classes¶

Class

Description

PaCMAPTable

A procedural table where a column in the input table column has been has dimensionally reduced by the PaCMAP algorithm.

Data¶

Data

Description

pacmap

API¶

class PaCMAPTable(
*,
url: Url | None = None,
created: str | None = None,
description: str | None = None,
row_cache_url: Url | None = None,
row_cache_populated: bool | None = None,
input_table_url: Url | Table | None = None,
source_embedding_column: str | None = None,
target_embedding_column: str | None = None,
retain_source_embedding_column: bool | None = None,
fit_table_url: Table | Url | None = None,
model_url: Url | None = None,
n_components: int | None = None,
n_neighbors: int | None = None,
MN_ratio: float | None = None,
FP_ratio: float | None = None,
distance: str | None = None,
lr: float | None = None,
num_iters: int | None = None,
verbose: bool | None = None,
apply_pca: bool | None = None,
random_state: int | None = None,
init_parameters: Any = None,
standard_scaler_normalize: bool | None = None,
input_tables: list[Url] | None = None,
)¶

Bases: tlc.core.objects.tables.from_table.dimensional_reduction_table._DimensionalReductionTable

A procedural table where a column in the input table column has been has dimensionally reduced by the PaCMAP algorithm.

Creates a derived table with a new column containing the dimensionally reduced data.

Parameters:

  • url – The URL of the table.

  • created – The date and time the table was created.

  • description – A description of the table.

  • row_cache_url – The URL of the row cache.

  • row_cache_populated – Whether the row cache has been populated.

  • input_table_url – The input table to apply the dimensionality reduction to

  • source_embedding_column – The column in the input table to apply dimensionality reduction to

  • target_embedding_column – The name of the new column to create in the output table

  • retain_source_embedding_column – Whether to retain the source column in the input table, defaults to False

  • standard_scaler_normalize – Whether to apply the sklearn standard scaler to input before reducing, defaults to False

  • fit_table_url – The table to use for fitting reduction transform. If not specified, the input table is used.

  • model_url – The URL to store/load the reducer model file. If empty, no model is saved.

  • n_components – The dimension of the output embedding

  • random_state – The random seed for the reducer algorithm

  • init_parameters – The parameters used to initialize the table.

  • input_tables – Optional list of Tables or URLs to record as input tables for lineage tracking.

algorithm_name = PaCMAP¶
pacmap = _lazy_import(...)¶