fixed_combinations_constraint

Constraint: only observed column combinations are valid

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

fixed_combinations_constraint function

<dl><dt>columns</dt>
<dd>Character vector of column names.</dd>
<dt>reference_data</dt>
<dd>Data frame containing the allowed combinations.</dd></dl>

Arguments

Constraint: only observed column combinations are valid — fixed_combinations_constraint

<dl>

<dt>columns</dt>
<dd>Character vector of column names.</dd>


<dt>reference_data</dt>
<dd>Data frame containing the allowed combinations.</dd>

</dl>

fixed_combinations_constraint: Constraint: only observed column combinations are valid

Description

Usage

Value

Arguments

Examples