cca-zoo 2.3.6

Canonical Correlation Analysis Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic methods in a scikit-learn style framework

CCA-Zoo

Unlock the hidden relationships in multiview data.

In an era inundated with data, unraveling the intricate connections between different data views is paramount. CCA-Zoo emerges as the definitive toolkit for this, offering an extensive suite of linear, kernel, and deep methods for canonical correlation analysis.

Inspired by the simplicity and effectiveness of scikit-learn and mvlearn, CCA-Zoo offers a seamless experience with its fit/transform/fit_transform methods.

Table of Contents

• Installation
• Documentation
• Citation
• Contributions
• Sources

🚀 Get Started in 5 Minutes

Installation

Whether you're a pip enthusiast or a poetry lover, we've got you covered:

pip install cca-zoo
# or for the adventurous
pip install cca-zoo[probabilistic]

Poetry aficionados can dive in with:

poetry add cca-zoo
# or with a twist of probability
poetry add cca-zoo[probabilistic]

📚 Dive Deep

Embark on a journey through multiview correlations with our comprehensive guide.

🙏 Show Your Love

CCA-Zoo thrives on the support of its community. If it's made a splash in your research, consider sprinkling some stardust by citing our JOSS paper or simply starring our repo. Every gesture counts!

📜 Chapman et al., (2021). CCA-Zoo: A collection of Regularized, Deep Learning based, Kernel, and Probabilistic CCA methods in a scikit-learn style framework. Journal of Open Source Software, 6(68), 3823, Link.

👩‍💻 Contribute

Every idea, every line of code adds value. Check out our contribution guide and help CCA-Zoo soar to new heights!

🙌 Props

A nod to the stalwarts and pioneers whose work paved the way. Dive into their implementations and explorations:

• Regularised CCA/PLS: MATLAB
• Sparse PLS: MATLAB SPLS
• DCCA/DCCAE: Keras DCCA, Torch DCCA, and more...
• VAE: Torch VAE