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APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering smoother and interpretable predictions.

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APLR

Automatic Piecewise Linear Regression

About

APLR allows you to build predictive and interpretable regression or classification machine learning models in Python, using the Automatic Piecewise Linear Regression (APLR) methodology developed by Mathias von Ottenbreit. APLR often rivals tree-based methods in predictive accuracy, while offering smoother, more interpretable predictions.

For further details, see the documentation. You may also read the published article for additional insights: Link 1 and Link 2. Additional functionality has been added since the article was published.

Installation

To install APLR, use the following command:

pip install aplr

Availability

APLR is available for Windows, most Linux distributions, and macOS.

Usage

Example Python scripts are available here.

Sponsorship

Consider sponsoring Von Ottenbreit Data Science by clicking the Sponsor button on the repository. Sufficient funding will help maintain and further develop APLR.

API Reference

Contact Information

For inquiries, please email: [email protected]