Struct WeightLearner 

pub struct WeightLearner { /* private fields */ }

Weight learner for EnsembleNER.

Learns optimal backend weights from evaluation data.

Example

use anno::backends::ensemble::{EnsembleNER, WeightLearner};

let mut learner = WeightLearner::new();

// Add training examples from gold data
for (text, gold_entities) in gold_data {
    learner.add_examples(&text, &gold_entities, &backends);
}

// Learn weights
let learned_weights = learner.learn_weights();

// Create ensemble with learned weights
let ensemble = EnsembleNER::new().with_weights(learned_weights);

Implementations

impl WeightLearner

pub fn new() -> Self

Create a new weight learner.

pub fn with_smoothing(self, smoothing: f64) -> Self

Set smoothing factor.

pub fn add_example(&mut self, example: &WeightTrainingExample)

Add a training example.

pub fn add_from_backends( &mut self, text: &str, gold_entities: &[Entity], backends: &[(&str, &dyn Model)], )

Add examples from gold entities and backend predictions.

Runs each backend on the text and compares to gold entities.

pub fn learn_weights(&self) -> HashMap<String, BackendWeight>

Learn optimal weights from accumulated statistics.

Uses precision-based weighting with Laplace smoothing.

pub fn get_stats(&self, backend_name: &str) -> Option<&BackendStats>

Get statistics for a backend.

pub fn backend_names(&self) -> Vec<&String>

Get all backend names.

Trait Implementations

impl Default for WeightLearner

fn default() -> Self

Returns the “default value” for a type.