GeezerVisonThe World Wide Web, restored to 800 pixels of glory. |
| Home|About|Gaming cabinet|Archives|How it works|Starter sites |
GeezerVison is showing github.com — feast-gcp-driver-ranking-tutorial/predict.py at master · feast-dev/feast-gcp-driver-ranking-tutorial Expand file tree/ Copy pathpredict.pyMore file actions 40 lines (31 loc) · 1.14 KB / Copy pathpredict.pyFile metadata and controls40 lines (31 loc) · 1.14 KB 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 import pandas as pd import feast from joblib import load class DriverRankingModel: def __init__(self): # Load model self.model = load("driver_model.bin") # Set up feature store self.fs = feast.FeatureStore(repo_path="driver_ranking/") def predict(self, driver_ids): # Read features from Feast driver_features = self.fs.get_online_features( entity_rows=[{"driver_id": driver_id} for driver_id in driver_ids], feature_refs=[ "driver_hourly_stats:conv_rate", "driver_hourly_stats:acc_rate", "driver_hourly_stats:avg_daily_trips", ], ) df = pd.DataFrame.from_dict(driver_features.to_dict()) # Make prediction df["prediction"] = self.model.predict(df[sorted(df)]) # Choose best driver best_driver_id = df["driver_id"].iloc[df["prediction"].argmax()] # return best driver return best_driver_id if __name__ == "__main__": drivers = [1001, 1002, 1003, 1004] model = DriverRankingModel() best_driver = model.predict(drivers) print(best_driver) |
| You are visitor 01402520 — GeezerVison does not store the pages you look up. Best viewed with Netscape Navigator 4.7 or Internet Explorer 6 at 800×600. No cookies required. |