MBPLS

Spec sheet

Purpose

MBPLS is a Python package for Partial Least Squares prediction modeling with univariate or multivariate outcomes.Read 12 Oct 2026 · mbpls.readthedocs.io

Free plan

YesRead 24 Sep 2026 · mbpls.readthedocs.io

License

The project repository identifies its license as BSD-3-Clause.Read 12 Oct 2026 · github.com

Algorithms

The package provides KERNEL, NIPALS, and UNIPALS for multiblock modeling, as well as SIMPLS for fast predictions.Read 12 Oct 2026 · mbpls.readthedocs.io

Block contribution

The introduction example says MB-PLS provides a measure of how much each X block contributes to predicting Y.Read 12 Oct 2026 · mbpls.readthedocs.io

Dependencies

The installation instructions say some dependencies may require upgrades, naming scikit-learn, numpy, and scipy.Read 12 Oct 2026 · mbpls.readthedocs.io

Examples

The documentation links to real-world Jupyter Notebook examples in the project's GitHub repository.Read 12 Oct 2026 · mbpls.readthedocs.io

Installation

The documentation gives `pip install mbpls` as the Python 3 installation command.Read 12 Oct 2026 · mbpls.readthedocs.io

Intended fields

The repository lists bioinformatics, chemometrics, data fusion, metabolomics, and machine learning among its topics.Read 12 Oct 2026 · github.com

Large matrices

The documentation says its algorithms are optimized for robust performance on large data matrices.Read 12 Oct 2026 · mbpls.readthedocs.io

Missing data

The package documentation says it is designed to handle missing data.Read 12 Oct 2026 · mbpls.readthedocs.io

Model methods

The MBPLS class supports fitting, prediction, transforming data, and plotting model values.Read 12 Oct 2026 · mbpls.readthedocs.io

Multiple data blocks

MBPLS predicts a response vector or matrix from multiple data blocks.Read 12 Oct 2026 · mbpls.readthedocs.io

Outcomes

It supports prediction of univariate or multivariate outcomes.Read 12 Oct 2026 · mbpls.readthedocs.io

Plotting

The quick-start example uses a built-in plot method for exploratory analysis of multiblock PLS models.Read 12 Oct 2026 · mbpls.readthedocs.io

Regression models

YesRead 24 Sep 2026 · mbpls.readthedocs.io

Scikit-learn API

The package uses an interface described as compatible with the commonly known Scikit-learn API and its model selection toolbox.Read 12 Oct 2026 · mbpls.readthedocs.io

Scikit-learn interface

The package uses a commonly known Scikit-learn API and its model selection toolbox.Read 12 Oct 2026 · mbpls.readthedocs.io

Scripting support

YesRead 24 Sep 2026 · mbpls.readthedocs.io

Sparse data limit

NIPALS is the only documented algorithm that handles sparse data, and sparse_data must be set to True to allow it.Read 12 Oct 2026 · mbpls.readthedocs.io

Where Specifiction places it

• Statistical Analysis Software#100 of 1066.9