Struct DiversityBasedSampling 

pub struct DiversityBasedSampling {
    pub batch_size: usize,
    pub diversity_method: String,
    pub distance_metric: String,
    pub kernel_bandwidth: f64,
    pub regularization: f64,
    pub max_iter: usize,
    pub random_state: Option<u64>,
}

Diversity-Based Sampling for active learning

This method focuses purely on selecting diverse samples from the unlabeled data using various diversity measures including determinantal point processes (DPP), maximum marginal relevance (MMR), and clustering-based approaches.

Fields

batch_size: usize

batch_size

diversity_method: String

diversity_method

distance_metric: String

distance_metric

kernel_bandwidth: f64

kernel_bandwidth

regularization: f64

regularization

max_iter: usize

max_iter

random_state: Option<u64>

random_state

Implementations

impl DiversityBasedSampling

pub fn new() -> Self

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

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

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

pub fn kernel_bandwidth(self, kernel_bandwidth: f64) -> Self

pub fn regularization(self, regularization: f64) -> 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 DiversityBasedSampling

fn clone(&self) -> DiversityBasedSampling

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for DiversityBasedSampling

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

Formats the value using the given formatter.

impl Default for DiversityBasedSampling

fn default() -> Self

Returns the “default value” for a type.