semvec/pypi-packages huggingface dataset:
conditional-kde 0.1.2
Conditional Kernel Density Estimation.
License: MIT
Requires Python: >=3.9
Keywords: conditional_kde, kernel density estimation, machine learning

===============
Conditional KDE
===============

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Conditional Kernel Density Estimation
-------------------------------------

A Python package for conditional kernel density estimation. This library provides efficient implementations for estimating conditional probability densities using kernel methods.

* **Free software:** MIT license
* **Documentation:** https://conditional-kde.readthedocs.io
* **PyPI:** https://pypi.org/project/conditional_kde/
* **Source Code:** https://github.com/dprelogo/conditional_kde


Installation
------------

Install from PyPI::

    pip install conditional_kde

For development installation::

    git clone https://github.com/dprelogo/conditional_kde.git
    cd conditional_kde
    pip install -e .[dev]


Quick Start
-----------

.. code-block:: python

    from conditional_kde import ConditionalKDE

    # Example usage
    ckde = ConditionalKDE()
    # Add your code example here


Features
--------

* Gaussian and interpolated kernel density estimation
* Support for conditional density estimation
* Efficient implementation using NumPy and SciPy
* Comprehensive test coverage
* Type hints for better IDE support

Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage