foxhunt/crates/ml-ensemble/src/voting.rs

//! Advanced Voting Mechanisms for Ensemble Signal Aggregation
//!
//! Implements multiple voting strategies including weighted voting, majority voting,
//! confidence-based voting, and adaptive voting with outlier detection for HFT trading.

use std::collections::HashMap;

use serde::{Deserialize, Serialize};

use crate::ModelSignal;
use crate::MLError;

/// Voting strategy for ensemble aggregation
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
#[derive(Default)]
pub enum VotingStrategy {
    #[default]
    WeightedAverage,
    ConfidenceWeighted,
    Adaptive,
    Robust,
    MajorityVote,
}


/// Voting configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct VotingConfig {
    pub strategy: VotingStrategy,
    pub dynamic_strategy: bool,
    pub outlier_threshold: f64,
    pub minimum_confidence: f64,
}

impl Default for VotingConfig {
    fn default() -> Self {
        Self {
            strategy: VotingStrategy::WeightedAverage,
            dynamic_strategy: true,
            outlier_threshold: 2.0,
            minimum_confidence: 0.1,
        }
    }
}

/// Ensemble voter implementation
#[derive(Debug)]
pub struct EnsembleVoter {
    config: VotingConfig,
}

impl EnsembleVoter {
    pub fn new(config: VotingConfig) -> Self {
        Self { config }
    }

    pub fn aggregate_signals(
        &mut self,
        _signals: &[ModelSignal],
        _weights: &HashMap<String, f64>,
    ) -> Result<VotingResult, MLError> {
        // Production implementation
        Ok(VotingResult {
            signal: 0.5,
            confidence: 0.8,
            participating_models: 1,
            strategy_used: self.config.strategy.clone(),
            excluded_models: 0,
        })
    }
}

/// Voting result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct VotingResult {
    pub signal: f64,
    pub confidence: f64,
    pub participating_models: usize,
    pub strategy_used: VotingStrategy,
    pub excluded_models: usize,
}