Instructions to use yanyoeurn/phishing-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use yanyoeurn/phishing-detector with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("yanyoeurn/phishing-detector", "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
| accuracy,precision,recall,f1,roc_auc,train_time_seconds,train_samples,test_samples,feature_count,algorithm | |
| 0.7774380431284197,0.9389993145990404,0.5142642642642643,0.6645646373999515,0.8937486782557206,116.286367,24852,6214,5051,logistic_regression | |
| 0.5704859993562923,0.49949238578680205,0.9234234234234234,0.6483067597838977,0.7793457894514232,0.230336,24852,6214,5051,naive_bayes | |
| 0.7565175410363695,0.9644874899112187,0.4485735735735736,0.6123494747630028,0.8792496193376473,7.407008,24852,6214,5051,random_forest | |