Extracting, Computing and Exploring the Parameters of Statistical Models using R
Extracting, Computing and Exploring the Parameters of Statistical Models using R - Published in JOSS (2020)
VIP
VIP: A Python package for high-contrast imaging - Published in JOSS (2023)
BetaML
BetaML: The Beta Machine Learning Toolkit, a self-contained repository of Machine Learning algorithms in Julia - Published in JOSS (2021)
ExpFamilyPCA.jl
ExpFamilyPCA.jl: A Julia Package for Exponential Family Principal Component Analysis - Published in JOSS (2025)
xeofs
xeofs: Comprehensive EOF analysis in Python with xarray - Published in JOSS (2024)
prince
:crown: Multivariate exploratory data analysis in Python — PCA, CA, MCA, MFA, FAMD, GPA
omicspls
R package for High dimensional data analysis and integration with O2PLS!
plnmodels
A collection of Poisson lognormal models for multivariate count data analysis
h2o
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
knrscore
KNRScore is a Python package for computing K-Nearest-Rank Similarity, a metric that quantifies local structural similarity between two maps or embeddings.
SNPRelate
R package: parallel computing toolset for relatedness and principal component analysis of SNP data (Development version only)
unsupervised_analysis
A general purpose Snakemake workflow and MrBiomics module to perform unsupervised analyses (dimensionality reduction & cluster analysis) and visualizations of high-dimensional data.
bibmon
Python package that provides predictive models for fault detection, soft sensing, and process condition monitoring.
https://github.com/bchao1/fun-with-mnist
Playing with MNIST. Machine Learning. Generative Models.
msmbuilder
:building_construction: Statistical models for biomolecular dynamics :building_construction:
r-sparsepca
Sparse Principal Component Analysis (SPCA) using Variable Projection
https://github.com/chris-santiago/decomposition
Simple ISOMAP and PCA decomposition algorithms
https://github.com/cheminfo/compass
Strategy for improved characterisation of human metabolic phenotypes using a COmbined Multiblock Principal components Analysis with Statistical Spectroscopy (COMPASS)
DiRe - JAX
DiRe - JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale Data - Published in JOSS (2025)
https://github.com/aariq/pca-vs-pls
Research compendium for "Using the right tool for the job: understanding the difference between unsupervised and supervised analyses of multivariate ecological data."
high-dimensional-analysis-in-python
Exploring and Modeling High-Dimensional Data
https://github.com/atharvapathak/telecom_churn_case_study
Build a classification model for reducing the churn rate for a telecom company
exploring-cybersecurity-data-science
Exploring Cybersecurity Data Science: Dimensionality Reduction and Cluster Analysis
https://github.com/danymukesha/pca-pwa
simplified manner for insights and decision-making by visualizing complex relationships with PCA web application
https://github.com/abel-research/openlimbtt
An Open-Source, synthetic transtibial residual limb anatomic dataset
https://github.com/abel-research/openhands
An Open-Source, synthetic finger anatomic dataset
OnlinePCA.jl: A Julia Package for Out-of-core and Sparse Principal Component Analysis
OnlinePCA.jl: A Julia Package for Out-of-core and Sparse Principal Component Analysis - Published in JOSS (2026)
https://github.com/databio/cocoa
Annotating epigenetic variation among samples with region sets in R