oxirs-vec 0.2.4

//! Machine learning models for intelligent caching decisions

use anyhow::Result;
use std::collections::HashMap;
use std::time::SystemTime;

use super::types::{
    AccessPredictionModel, CacheKey, CacheValue, EvictionTimingModel, FeatureExtractor,
    HitProbabilityModel, OptimizationObjective, TierPlacementModel,
};

/// Machine learning models for intelligent caching decisions
#[derive(Debug)]
pub struct MLModels {
    /// Access pattern prediction model
    access_predictor: AccessPredictionModel,
    /// Cache hit probability model
    hit_probability_model: HitProbabilityModel,
    /// Optimal tier placement model
    pub(crate) tier_placement_model: TierPlacementModel,
    /// Eviction timing model
    eviction_timing_model: EvictionTimingModel,
}

impl MLModels {
    pub fn new() -> Result<Self> {
        Ok(Self {
            access_predictor: AccessPredictionModel {
                model_weights: vec![1.0, 0.8, 0.6, 0.4],
                feature_extractors: vec![
                    FeatureExtractor::AccessFrequency,
                    FeatureExtractor::RecencyScore,
                    FeatureExtractor::SizeMetric,
                    FeatureExtractor::ComputationCost,
                ],
                prediction_accuracy: 0.75,
            },
            hit_probability_model: HitProbabilityModel {
                probability_matrix: HashMap::new(),
                model_confidence: 0.8,
                last_update: SystemTime::now(),
            },
            tier_placement_model: TierPlacementModel {
                placement_scores: HashMap::new(),
                optimization_objective: OptimizationObjective::BalancedPerformance,
            },
            eviction_timing_model: EvictionTimingModel {
                survival_functions: HashMap::new(),
                hazard_rates: HashMap::new(),
            },
        })
    }

    pub fn update_with_store_event(&mut self, _key: &CacheKey, _value: &CacheValue, _tier: u32) {
        // Implementation would update ML models with new data
    }
}

impl TierPlacementModel {
    pub fn predict_optimal_tier(&self, _key: &CacheKey, _value: &CacheValue) -> u32 {
        // Simplified: for now just return tier 0 (fastest)
        0
    }
}