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kernel density estimation backed by a C extension

Project description

kern

kern is a minimalistic kernel density estimation package backed by optimized C implementations. It provides exact, approximate, bounded, and multivariate KDE estimators with a scikit-learn-like API.

Installation

python -m pip install kern_kde

Example usage

from kern import KernelDensity

model = KernelDensity(bandwidth=0.3).fit([0.0, 0.2, 1.0])
density = model.evaluate([0.1, 0.5])

See the documentation for the user guide, API reference, and source-build options.

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