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small-data-ml

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nsdmlk / SmallGBM

SmallGBM is a gradient boosting library designed for small datasets (n < 1000). It combines robust leaf weight estimation with stochastic split selection to outperform XGBoost and LightGBM — with lower variance, no hyperparameter tuning, and a native C core.

machine-learning c-language gradient-boosting small-data small-data-ml

Updated Sep 30, 2026
Jupyter Notebook

amaxiom / SelectOmics

A reproducible, leakage-proof feature selector for omics classification. Find the right features in n<<p data, not just fewer of them.

machine-learning regression high-dimensional-data feature-selection classification dimensionality-reduction omics imbalanced-data small-dataset imbalance high-dimensionality omics-analysis small-data small-datasets omics-data-analysis small-data-ml small-data-machine-learning

Updated Sep 22, 2026
Python

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