Conditional KDE
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
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 hereFeatures
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.
1 maintainer
Metadata
1 maintainer
Release files for conditional-kde 0.1.2
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Total release size: 55.1 kB
Release files / conditional_kde-0.1.2.tar.gz
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