conditional-kde 0.1.2

Conditional Kernel Density Estimation.

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

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.