Struct CoreSetApproach 

pub struct CoreSetApproach {
    pub batch_size: usize,
    pub distance_metric: String,
    pub initialization: String,
    pub max_iter: usize,
    pub random_state: Option<u64>,
}

Core-set approach for batch active learning

This method selects a batch of samples that best represents the unlabeled data distribution, acting as a “core-set” or summary of the data.

Fields

batch_size: usize

batch_size

distance_metric: String

distance_metric

initialization: String

initialization

max_iter: usize

max_iter

random_state: Option<u64>

random_state

Implementations

impl CoreSetApproach

pub fn new() -> Self

pub fn batch_size(self, batch_size: usize) -> Result<Self>

pub fn distance_metric(self, distance_metric: String) -> Self

pub fn initialization(self, initialization: String) -> Self

pub fn max_iter(self, max_iter: usize) -> Self

pub fn random_state(self, random_state: u64) -> Self

pub fn query( &self, X: &ArrayView2<'_, f64>, _probabilities: &ArrayView2<'_, f64>, ) -> Result<Vec<usize>>

Trait Implementations

impl Clone for CoreSetApproach

fn clone(&self) -> CoreSetApproach

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CoreSetApproach

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

Formats the value using the given formatter.

impl Default for CoreSetApproach

fn default() -> Self

Returns the “default value” for a type.