scirs2_integrate/realtime_performance_adaptation/
predictor.rs

1//! Performance prediction implementation
2//!
3//! This module contains the implementation for predictive performance modeling
4//! and machine learning-based optimization.
5
6use super::types::*;
7use crate::common::IntegrateFloat;
8use crate::error::{IntegrateError, IntegrateResult};
9
10impl<F: IntegrateFloat> PerformancePredictor<F> {
11    /// Create a new performance predictor
12    pub fn new() -> Self {
13        Self {
14            model_registry: ModelRegistry::default(),
15            feature_engineering: FeatureEngineering::default(),
16            model_trainer: ModelTrainer::default(),
17            accuracy_tracker: PredictionAccuracyTracker::default(),
18        }
19    }
20
21    /// Predict performance for given configuration
22    pub fn predict_performance(
23        &self,
24        _config: &AdaptationStrategy<F>,
25    ) -> IntegrateResult<PredictedPerformance> {
26        // Implementation would go here
27        Ok(PredictedPerformance::default())
28    }
29
30    /// Update models with new performance data
31    pub fn update_models(&mut self, metrics: &PerformanceMetrics) -> IntegrateResult<()> {
32        // Implementation would go here
33        Ok(())
34    }
35}
36
37impl<F: IntegrateFloat + Default> MachineLearningOptimizer<F> {
38    /// Create a new ML optimizer
39    pub fn new() -> Self {
40        Self {
41            rl_agent: ReinforcementLearningAgent::default(),
42            bayesian_optimizer: BayesianOptimizer::default(),
43            nas_engine: NeuralArchitectureSearch::default(),
44            hyperopt_engine: HyperparameterOptimizer::default(),
45        }
46    }
47
48    /// Optimize parameters using ML
49    pub fn optimize_parameters(
50        &mut self,
51        _metrics: &PerformanceMetrics,
52    ) -> IntegrateResult<OptimizationResult<F>> {
53        // Implementation would go here
54        Ok(OptimizationResult::default())
55    }
56}
57
58impl<F: IntegrateFloat + Default> Default for PerformancePredictor<F> {
59    fn default() -> Self {
60        Self::new()
61    }
62}
63
64impl<F: IntegrateFloat + Default> Default for MachineLearningOptimizer<F> {
65    fn default() -> Self {
66        Self::new()
67    }
68}
scirs2_integrate/realtime_performance_adaptation/predictor.rs

scirs2_integrate/realtime_performance_adaptation/
predictor.rs
