Struct BatchModeActiveLearning 

pub struct BatchModeActiveLearning {
    pub batch_size: usize,
    pub diversity_weight: f64,
    pub strategy: String,
    pub distance_metric: String,
    pub random_state: Option<u64>,
}

Batch Mode Active Learning using uncertainty and diversity

This method selects a batch of samples by balancing uncertainty (information gain) and diversity (avoiding redundant samples) using various strategies.

Fields

batch_size: usize

batch_size

diversity_weight: f64

diversity_weight

strategy: String

strategy

distance_metric: String

distance_metric

random_state: Option<u64>

random_state

Implementations

impl BatchModeActiveLearning

pub fn new() -> Self

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

pub fn diversity_weight(self, diversity_weight: f64) -> Result<Self>

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

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

fn clone(&self) -> BatchModeActiveLearning

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for BatchModeActiveLearning

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

Formats the value using the given formatter.

impl Default for BatchModeActiveLearning

fn default() -> Self

Returns the “default value” for a type.