load_metadata

Generates synthetic tabular data from real datasets using
Gaussian copula models, with parametric marginal selection for
numerical columns and a cumulative-frequency embedding that brings
categorical and boolean columns into the same joint copula. Includes
a metadata system with column types and primary keys, declarative
constraints enforced via rejection sampling, conditional sampling,
and quality, validity and privacy reports modeled on those of the
'SDMetrics' library. Inspired by the Python 'SDV' (Synthetic Data
Vault) library by 'DataCebo'; see Patki, Wedge and Veeramachaneni
(2016) "The Synthetic Data Vault" <doi:10.1109/DSAA.2016.49>.

Kailas Venkitasubramanian

rsdv

Synthetic Tabular Data Generation with Gaussian Copulas

load_metadata function

<dl><dt>path</dt>
<dd>Path to a JSON file produced by <code>save_metadata()</code>.</dd></dl>

Arguments

Load metadata from a JSON file — load_metadata

<dl>

<dt>path</dt>
<dd>Path to a JSON file produced by <code>save_metadata()</code>.</dd>

</dl>

load_metadata: Load metadata from a JSON file

Description

Usage

Value

Arguments

Examples