How to use the copulas.univariate.GaussianUnivariate function in copulas

To help you get started, we’ve selected a few copulas examples, based on popular ways it is used in public projects.

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github HDI-Project / SDV / sdv / sdv.py View on Github external
# -*- coding: utf-8 -*-

"""Main module."""
import pickle

from copulas.univariate import GaussianUnivariate

from sdv.metadata import Metadata
from sdv.modeler import Modeler
from sdv.models.copulas import GaussianCopula
from sdv.sampler import Sampler

DEFAULT_MODEL = GaussianCopula
DEFAULT_MODEL_KWARGS = {
    'distribution': GaussianUnivariate
}


class NotFittedError(Exception):
    pass


class SDV:
    """Automated generative modeling and sampling tool.

    Allows the users to generate synthetic data after creating generative models for their data.

    Args:
        model (type):
            Class of the ``copula`` to use. Defaults to
            ``sdv.models.copulas.GaussianCopula``.

copulas

Create tabular synthetic data using copulas-based modeling.

BSL-1.0
Latest version published 13 days ago

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