Instructions to use SharleyK/predictive-maintenance-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use SharleyK/predictive-maintenance-model with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("SharleyK/predictive-maintenance-model", "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
File size: 488 Bytes
ab6d575 e1e4438 ab6d575 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"model_name": "AdaBoost",
"parameters": {
"learning_rate": 0.05,
"n_estimators": 100
},
"performance": {
"test_accuracy": 0.6667519836191451,
"test_precision": 0.6854040242733951,
"test_recall": 0.8712951684937068,
"test_f1": 0.7672506256703611,
"test_roc_auc": 0.6959420475671518
},
"training_date": "2026-02-08 16:01:01",
"feature_count": 17,
"training_samples": 15628,
"test_samples": 3907
} |