GitHub

GitHub - kossisoroyce/timber: Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code ...

Timber takes a trained ML model — XGBoost, LightGBM, scikit-learn, CatBoost, ONNX (tree ensembles, linear models, SVMs, k-NN, Naive Bayes, GPR, Isolation Forest), or a URDF robot description — runs it ...
IEEE

Analysis of Tree-Family Machine Learning Techniques for Risk Prediction in Software Requirements

Abstract: Risk prediction is the most sensitive and critical activity in the Software Development Life Cycle (SDLC). It might determine whether the project succeeds or fails. To increase the success ...