File size: 1,223 Bytes
bfb8a00 | 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 41 42 43 | import json
from pathlib import Path
import numpy as np
MODEL_PATH = Path("sample_maintenance_model.json")
RECORD_PATH = Path("sample_record.json")
def sigmoid(value):
value = np.clip(value, -30, 30)
return 1.0 / (1.0 + np.exp(-value))
def score_record(record, payload, threshold=0.5):
feature_names = payload["feature_names"]
values = np.array([[float(record.get(name, 0.0)) for name in feature_names]], dtype=float)
scaler = payload.get("scaler")
if scaler:
mean = np.array(scaler["mean"], dtype=float)
scale = np.array(scaler["scale"], dtype=float)
values = (values - mean) / scale
weights = np.array(payload["weights"], dtype=float)
probability = float(sigmoid((values @ weights) + payload["bias"])[0])
return {
"score": round(probability, 4),
"label": "review" if probability >= threshold else "standard",
"threshold": threshold,
}
def main():
payload = json.loads(MODEL_PATH.read_text(encoding="utf-8"))
record = json.loads(RECORD_PATH.read_text(encoding="utf-8"))
print(json.dumps(score_record(record, payload), indent=2))
if __name__ == "__main__":
main()
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