Tabular Regression
Scikit-learn
PyTorch
custom
gradient-boosting
machine-learning
research-paper
lightgbm
benchmark
Instructions to use MohammadMurtuza/enhanced-gradient-boosting-research with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use MohammadMurtuza/enhanced-gradient-boosting-research with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("MohammadMurtuza/enhanced-gradient-boosting-research", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
| from dataset_generator import create_extended_dataset | |
| # Generate dataset | |
| X, y = create_extended_dataset(n_samples=50000, random_state=42) | |
| print(f"Dataset shape: {X.shape}") | |
| print(f"Target range: [{y.min():.2f}, {y.max():.2f}]") | |
| print("Ready for model training!") |