sisl/ExpFamilyPCA.jl

A Julia package for exponential family principal component analysis (EPCA).

44
/ 100
Emerging

This tool helps scientists, data analysts, and machine learning practitioners simplify complex datasets that don't fit the standard 'bell curve' mold. It takes in various types of raw data, like binary choices, counts, or survival times, and reduces it into a smaller, more manageable representation while preserving key information. The output is a compressed version of your data, making it easier to analyze, visualize, or use in other models.

Use this if you need to reduce the complexity of high-dimensional data that includes non-Gaussian distributions such as binary, count, or compositional data.

Not ideal if your data is exclusively real-valued and well-described by a Gaussian (normal) distribution, as standard PCA might suffice.

data-analysis dimensionality-reduction machine-learning signal-processing statistical-modeling
No Package No Dependents
Maintenance 10 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 13 / 25

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Stars

10

Forks

2

Language

Julia

License

MIT

Last pushed

Mar 09, 2026

Commits (30d)

0

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