Pca Python Packages

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.

pca

pca: A Python Package for Principal Component Analysis.

ellama

Embeddings interface for Ollama

xeofs

Comprehensive EOF analysis in Python with xarray: A versatile, multidimensional, and scalable tool for advanced climate data analysis

palos

Misc Python modules developed and used by the yfish group

h2o-client

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.

qgrain

An easy-to-use software for the comprehensive analysis of grain size distributions

nlptoolkit-classification

Machine learning library for classification tasks

torch-pca

Principal Component Anlaysis (PCA) in PyTorch.

bpca

Bayesian Principal Component Analysis in Python

vip-hci

VIP is a python package/library for angular, reference star and spectral differential imaging for exoplanet/disk detection through high-contrast imaging.

nlptoolkit-classification-cy

Machine learning library for classification tasks

calypso-emulator

Parameter-conditioned stochastic timeseries emulator for circumbinary accretion lightcurves

cvmatrix

Computation of training set (X^T * W * X) and (X^T * W * Y) or (X^T * X) and (X^T * Y) in a cross-validation setting using the fast algorithms by Engstrøm and Jensen (2025).

h2o-mlflow-flavor

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.

rustypca

Implements Probabilistic PCA by means of EM via rust

sklearn-utilities

Utilities for scikit-learn. Append prediction to x, append prediction to x single, append x prediction to x, compose var estimator, data frame wrapper, drop by noise prediction, drop missing rows y, dummy regressor var, estimator wrapper base, excluded column transformer pandas, feature union pandas, id transformer, included column transformer pand

pychemometrics

pyChemometrics - Objects for multivariate analysis of chemometric and metabonomic datasets

augmented-pca

Python implementations of supervised and adversarial linear factor models.

nexus-pcv

A CLI tool to perform a pre-change validation on Nexus Dashboard Insights.

bibmon

Python package that provides predictive models for fault detection, soft sensing, and process condition monitoring.

tasnif

Unsupervised image clustering with modern deep embeddings (CLIP, timm) + K-Means. Sort a folder of images into clusters with one Python call or CLI.

ppca-rs

Python+Rust implementation of the Probabilistic Principal Component Analysis model

chemometrics

Python library for chemometric data analysis