Pls Python Packages

process-improve

Python toolkit for analysis of industrial process data; multivariate analysis, designed experiments, process monitoring.

nirs4all

A library for Near Infrared Sprectroscopy prediction. NIRS ML. Rebuild of the Pinard package.

cca-zoo

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

ikpls

Fast CPU and GPU Python implementations of Improved Kernel Partial Least Squares (PLS) by Dayal and MacGregor (1997) and Fast Partition-Based Cross-Validation With Centering and Scaling for XTX and XTY by Engstrøm and Jensen (2025). This package also includes options to use sample weights for PLS modeling.

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).

pychemometrics

pyChemometrics - Objects for multivariate analysis of chemometric and metabonomic datasets

wai-ma

Python library of 2-dimensional matrix algorithms.

pls-cli

Minimalist and full configurable greetings and TODO list

mamsi

The Multi-assay Mass Spectrometry Integration Project

chemometrics

Python library for chemometric data analysis

scikit-opls

Orthogonal PLS (OPLS / OPLS-DA) with a scikit-learn-compatible API

sparse-pls

Sparse Partial Least Squares (Sparse PLS) Regression is a Python-based model that integrates dimensionality reduction with variable selection, enabling interpretable analysis of high-dimensional datasets.

pdstoolkit

A Python package to facilitate building process data science solutions including process modeling, monitoring, fault diagnosis, etc.