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import joblib
import numpy as np
import pandas as pd
from typing import List
class SecondaryModel:
def __init__(self):
self.scaler = joblib.load("scalers/secondary_scaler.joblib")
self.model = joblib.load("models/secondary_weights.joblib")
self.secondary_model_features = [
"machine_probability", "backspace_count_normalized", "typing_duration_normalized",
"letter_discrepancy_normalized", "cosine_sim_gpt35", "cosine_sim_gpt4o"
]
def preprocess_input(self, secondary_model_features: List[float]) -> pd.DataFrame:
features_df = pd.DataFrame(
[secondary_model_features], columns=self.secondary_model_features)
features_df[self.secondary_model_features] = self.scaler.transform(
features_df[self.secondary_model_features])
return features_df
def predict(self, secondary_model_features: List[float]):
return int(self.model.predict(self.preprocess_input(secondary_model_features))[0])
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