Function Dependency

2. **Simulate Risk Occurrence**: Determine which risks occur based on their probabilities. 3. **Calculate Risk Score**: Compute the overall risk score by combining the probabilities and impacts of the occurring risks. ### Example Python Co…

logging.basicConfig(level=logging.ERROR, format='%(asctime)s - %(levelname)s - %(message)s') # Load the model once model = SentenceTransformer('paraphrase-MiniLM-L6-v2') def vectorize_document(doc, retries=3, delay=1): for attempt in …

for meta, gt in zip(metadata, ground_truth): if all(meta[key] == gt[key] for key in gt.keys()): correct += 1 return (correct / total) * 100 # Example ground truth data ground_truth = [...] # list of dictionarie…

logger.error(f"Error getting user profile for {user.id}: {e}") raise # Example usage if __name__ == "__main__": username = "example_user" password = "example_password" user = authenticate_user(username, pas…

dense_scores_normalized = normalize_scores(dense_scores) # Calculate weighted sum of sparse and dense scores hybrid_scores = alpha * sparse_scores_normalized + (1 - alpha) * dense_scores_normalized return hybrid_sc…

print(f"Error Reduction: {error_reduction:.2f}%") # Example usage integrate_and_validate(6000, 6000) ``` ### Explanation 1. **Tune the Model**: The `tune_model` function refines the complexity thresholds and resizes the context windo…

```python import numpy as np from sklearn.metrics import accuracy_score from sklearn.ensemble import RandomForestClassifier from sklearn.model_selection import train_test_split import redis import logging # Set up logging configuration log…