Struct FitnessAggregator 

pub struct FitnessAggregator { /* private fields */ }

Aggregates partial/incremental feedback into fitness estimates

Implementations

impl FitnessAggregator

pub fn new(model: AggregationModel) -> Self

Create a new aggregator with the given model

pub fn model(&self) -> &AggregationModel

Get the aggregation model

pub fn set_generation(&mut self, generation: usize)

Set the current generation

pub fn get_stats(&self, id: &CandidateId) -> Option<&CandidateStats>

Get stats for a candidate

pub fn get_fitness(&self, id: &CandidateId) -> Option<f64>

Get current fitness estimate for a candidate (point estimate only)

For uncertainty information, use get_fitness_estimate() instead.

pub fn get_fitness_estimate(&self, id: &CandidateId) -> Option<FitnessEstimate>

Get fitness estimate with uncertainty quantification

Returns a FitnessEstimate containing the point estimate, variance, and confidence intervals.

pub fn comparisons(&self) -> &[ComparisonRecord]

Get access to comparison records (for Bradley-Terry MLE)

pub fn record_rating(&mut self, id: CandidateId, rating: f64)

Record a rating for a candidate

pub fn record_comparison(&mut self, winner: CandidateId, loser: CandidateId)

Record a pairwise comparison result

pub fn record_tie(&mut self, id_a: CandidateId, id_b: CandidateId)

Record a tie in pairwise comparison

pub fn record_batch_selection( &mut self, selected: &[CandidateId], not_selected: &[CandidateId], )

Record batch selection results

pub fn recompute_all(&mut self) -> HashMap<CandidateId, f64>

Recompute all fitness estimates from comparison history

This is useful for Bradley-Terry model which uses batch MLE, or after loading a session from checkpoint.

pub fn process_response( &mut self, response: &EvaluationResponse, ) -> Vec<(CandidateId, f64)>

Process an evaluation response and return updated fitness values

pub fn process_pairwise( &mut self, id_a: CandidateId, id_b: CandidateId, winner: Option<CandidateId>, ) -> Vec<(CandidateId, f64)>

Process a pairwise comparison with both candidate IDs

pub fn process_batch_selection( &mut self, all_candidates: &[CandidateId], selected: &[CandidateId], ) -> Vec<(CandidateId, f64)>

Process batch selection with full context

pub fn all_candidates(&self) -> Vec<CandidateId>

Get all candidate IDs with fitness estimates

pub fn comparison_count(&self) -> usize

Get the number of comparisons recorded

pub fn clear(&mut self)

Clear all recorded data

Trait Implementations

impl Clone for FitnessAggregator

fn clone(&self) -> FitnessAggregator

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for FitnessAggregator

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for FitnessAggregator

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for FitnessAggregator

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.