Struct NearestNeighborMetaModel 

pub struct NearestNeighborMetaModel { /* private fields */ }

The simplest useful meta-model: given a new corpus, return the best_config of the training record whose corpus-feature vector is closest in z-score-normalized Euclidean distance.

• Works with N ≥ 1 records.
• Deterministic; no hyperparameters.
• Degenerate features (zero variance across training records) are dropped from the distance computation at fit time so they don’t divide by zero or dominate via raw-scale inflation.

Implementations

impl NearestNeighborMetaModel

pub fn new() -> Self

pub fn records(&self) -> &[MetaTrainingRecord]

Borrow the training records — useful for introspecting what the model considers the nearest-neighbor candidate pool.

pub fn rank_candidates(&self, features: &CorpusFeatures) -> Vec<(usize, f64)>

Distance from a given feature vector to every stored record, sorted ascending. Returned as (record_index, distance) pairs.

Trait Implementations

impl Clone for NearestNeighborMetaModel

fn clone(&self) -> NearestNeighborMetaModel

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NearestNeighborMetaModel

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

Formats the value using the given formatter.

impl Default for NearestNeighborMetaModel

fn default() -> Self

Returns the “default value” for a type.

impl MetaModel for NearestNeighborMetaModel

fn fit(&mut self, records: &[MetaTrainingRecord])

Fit on a training set. Replacing any prior state.

fn predict(&self, features: &CorpusFeatures) -> PipelineConfig

Predict the config that should work best on a corpus with the given profile. Panics if fit has not been called with at least one record — callers should treat MetaModel as a trained object and front-load fit.

fn name(&self) -> &str

Short name for logs and model comparison.