Description:

pcax 0.1.0

pcax
Minimal Principal Component Analsys (PCA) implementation using jax.
The aim of this project is to provide a JAX-based PCA implementation, eliminating the need for unnecessary data transfer to CPU or conversions to Numpy. This can provide performance benefits when working with large datasets or in GPU-intensive workflow
Usage
import pcax

# Fit the PCA model with 3 components on your data X
state = pcax.fit(X, n_components=3)

# Transform X to its principal components
X_pca = pcax.transform(state, X)

# Recover the original X from its principal components
X_recover = pcax.recover(state, X_pca)

Installation
pcax can be installed from PyPI via pip
pip install pcax

Alternatively, it can be installed directly from the GitHub repository:
pip install git+git://github.com/alonfnt/pcax.git

License

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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