Engine Predictive Maintenance Model
Best model: GradientBoosting
F1 (test): 0.7657
Usage
import pickle, pandas as pd
with open('best_model.pkl', 'rb') as f:
model = pickle.load(f)
# X = pd.DataFrame([{
# 'engine_rpm': 2500, 'lub_oil_pressure': 4.2, 'fuel_pressure': 110,
# 'coolant_pressure': 1.2, 'lub_oil_temp': 95, 'coolant_temp': 88
# }])
# pred = model.predict(X)[0]
Notes
- Tuned via GridSearchCV (scoring=F1), metrics logged with MLflow.
- Downloads last month
- -
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("dhani10/engine-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