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| """ | |
| Pattern Analysis Learner - Placeholder Implementation | |
| This module will be fully implemented in Task 9 | |
| """ | |
| from typing import Dict, Any | |
| from sqlalchemy.orm import Session | |
| class PatternAnalysisLearner: | |
| """ | |
| Analyzes patterns in completed interviews to identify predictive questions | |
| and update selection weights. | |
| NOTE: This is a placeholder implementation for Task 12 (API endpoints). | |
| Full implementation will be completed in Task 9. | |
| """ | |
| def __init__(self, db_session: Session, min_dataset_size: int = 50): | |
| """ | |
| Initialize pattern analysis learner. | |
| Args: | |
| db_session: Database session | |
| min_dataset_size: Minimum number of completed interviews required | |
| """ | |
| self.db_session = db_session | |
| self.min_dataset_size = min_dataset_size | |
| self.low_value_threshold = 0.3 | |
| def analyze_patterns(self) -> Dict[str, Any]: | |
| """ | |
| Run pattern analysis on completed interviews. | |
| This is a placeholder that returns mock results. | |
| Full implementation in Task 9 will: | |
| 1. Query completed interviews with outcomes | |
| 2. Group by outcome (hired/rejected) | |
| 3. Identify question sequences in successful interviews | |
| 4. Calculate topic/type correlations with success | |
| 5. Update question selection weights | |
| 6. Flag low-value questions | |
| Returns: | |
| Dictionary with analysis results | |
| """ | |
| # Placeholder implementation | |
| return { | |
| "interviews_analyzed": 0, | |
| "questions_updated": 0, | |
| "low_value_questions": [], | |
| "message": "Pattern analysis not yet implemented (Task 9)" | |
| } | |
| def identify_predictive_questions(self, interviews) -> Dict[int, float]: | |
| """ | |
| Identify which questions best predict success. | |
| Placeholder implementation. | |
| Args: | |
| interviews: List of completed interviews | |
| Returns: | |
| Dictionary mapping question_id to predictive_score | |
| """ | |
| return {} | |
| def update_selection_weights(self, predictive_scores: Dict[int, float]): | |
| """ | |
| Update question selection weights in database. | |
| Placeholder implementation. | |
| Args: | |
| predictive_scores: Dictionary mapping question_id to predictive_score | |
| """ | |
| pass | |