Balsa: A Fast C++ Random Forest Classifier with Command-line and Python Interface

The Journal of Open Source Software, vol. 11, pp. 8778

Abstract

Random Forest classifiers are widely used machine learning methods that combine multiple decision trees to improve predictive accuracy and reduce overfitting (Breiman, 2001).While implementations like scikit-learn (Pedregosa et al., 2011) are popular in the Python ecosystem, operational processing environments often require high-performance C++ implementations that can handle large datasets efficiently while maintaining low memory footprints.

Authors 5

1. Tobias Borsdorff Aachen SRON Space Research Organization Netherlands

   Space Research Organisation Netherlands

   Affiliation as printed

   SRON Space Research Organization Netherlands

2. Denis de Leeuw Duarte
   Affiliation as printed

   Jigsaw B.V., The Netherlands

3. Joris van Zwieten
   Affiliation as printed

   Jigsaw B.V., The Netherlands

4. S. Mandal Aachen SRON Space Research Organization Netherlands

   Space Research Organisation Netherlands

   Affiliation as printed

   SRON Space Research Organization Netherlands

5. Jochen Landgraf Aachen SRON Space Research Organization Netherlands

   Space Research Organisation Netherlands

   Affiliation as printed

   SRON Space Research Organization Netherlands