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GitHub18d
Boostora is a Python package that simplifies the process of hyperparameter tuning and visualization for XGBoost models using Optuna and SHAP. - GitHub
Automated hyperparameter tuning with Optuna Visualization of hyperparameter optimization results Interpretation of model predictions using SHAP values Logging of results and plots with MLflow You can ...
IEEE27d
Tuning Function-Based Light Computational Adaptive Fixed-Time Control for Overhead Cranes With Multiple Uncertainites - IEEE Xplore
Overhead cranes are important transportation equipments in practice, however, their existing control methods have encountered many difficulties in applications due to the underactuation, input ...
C&EN10d
SAND: Automated Time-Domain Modeling of NMR Spectra Applied to Metabolite Quantification
Developments in untargeted nuclear magnetic resonance (NMR) metabolomics enable the profiling of thousands of biological samples. The exploitation of this rich source of information requires a ...
IEEE24d
Machine Learning Classifiers and Hyperparameter Tuning to Enhance Prediction of ASD: An Automated Django Application - IEEE Xplore
Autism Spectrum Disorder (ASD) impacts social interaction, communication, and behavior as a result of variations in brain development of children. Typically, symptoms manifest around the age of 2 and ...
GitHub24d
A Python package for automated hyperparameter sweeps on High Performance Computing (HPC) systems using Hydra configs and W&B tracking. - GitHub
hpc-sweep-manager/ ├── pyproject.toml # Modern Python packaging ├── README.md ├── LICENSE ├── requirements.txt ├── src/hpc_sweep_manager/ │ ├── __init__.py │ ├── cli/ # Command-line interface │ │ ├── ...