Module adaptive_ml_error_correction 

Real-time Adaptive Error Correction with Machine Learning

This module implements machine learning-driven adaptive error correction that learns from error patterns in real-time to optimize correction strategies. The system uses various ML techniques including neural networks, reinforcement learning, and online learning to continuously improve error correction performance.

Key features:

• Real-time syndrome pattern recognition using neural networks
• Reinforcement learning for optimal correction strategy selection
• Online learning for adaptive threshold adjustment
• Ensemble methods for robust error prediction
• Temporal pattern analysis for correlated noise
• Hardware-aware correction optimization

Structs

AdaptiveCorrectionResult

Result of adaptive error correction

AdaptiveMLConfig

Adaptive error correction configuration

AdaptiveMLErrorCorrection

Adaptive ML error correction system

CorrectionMetrics

Performance metrics for error correction

ErrorCorrectionAgent

Reinforcement learning agent for error correction

FeatureExtractor

Feature extractor for syndrome analysis

SyndromeClassificationNetwork

Neural network for syndrome classification

TrainingExample

Training example for supervised learning

Enums

FeatureExtractionMethod

Feature extraction method for syndrome analysis

LearningStrategy

Learning strategy for adaptive correction

MLModelType

Machine learning model type for error correction

Functions

benchmark_adaptive_ml_error_correction

Benchmark adaptive ML error correction