Struct GradientEmbeddingMethods 

pub struct GradientEmbeddingMethods {
    pub batch_size: usize,
    pub embedding_dim: usize,
    pub gradient_method: String,
    pub similarity_threshold: f64,
    pub learning_rate: f64,
    pub max_iter: usize,
    pub random_state: Option<u64>,
}

Gradient Embedding Methods for active learning

This method uses gradient information from the model to select informative batches. It considers both the gradients with respect to model parameters and embedding representations to identify samples that would provide maximum learning benefit.

Fields

batch_size: usize

batch_size

embedding_dim: usize

embedding_dim

gradient_method: String

gradient_method

similarity_threshold: f64

similarity_threshold

learning_rate: f64

learning_rate

max_iter: usize

max_iter

random_state: Option<u64>

random_state

Implementations

impl GradientEmbeddingMethods

pub fn new() -> Self

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

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

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

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

pub fn learning_rate(self, learning_rate: 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 GradientEmbeddingMethods

fn clone(&self) -> GradientEmbeddingMethods

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for GradientEmbeddingMethods

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

Formats the value using the given formatter.

impl Default for GradientEmbeddingMethods

fn default() -> Self

Returns the “default value” for a type.