benchm-ml
by szilard (personal account)
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.). (description from the project’s GitHub page)
Repository facts
- Stars
- 1,897
- Forks
- 326
- Open issues and pull requests
- 12
- Primary language
- R
- License
- MIT License (MIT)
- Owner
- szilard · Personal account
- Created
- Mar 28, 2015
- Last push
- Sep 16, 2022
Topics
Related projects
Projects that share this one’s GitHub topics.
Rank 1,083: h2oai/h2o-3
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM wi…
7,511 starsJupyter NotebookApache-2.0Last push Oct 18, 2026
Rank 7,876: jphall663/interpretable_machine_learning_with_python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
681 starsJupyter NotebookNo license file detectedLast push Jun 17, 2024
Rank 2,490: parrt/dtreeviz
A python library for decision tree visualization and model interpretation.
3,161 starsJupyter NotebookMITLast push Jan 2, 2026
Rank 2,387: mljar/mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
3,301 starsPythonMITLast push Oct 16, 2026
Rank 2,211: ml-tooling/ml-workspace
🛠 All-in-one web-based IDE specialized for machine learning and data science.
3,548 starsJupyter NotebookApache-2.0Last push Jul 26, 2024
Rank 1,824: microsoft/FLAML
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
4,409 starsJupyter NotebookMITLast push Oct 18, 2026