Struct SagOptimizer 

pub struct SagOptimizer {
    pub max_epochs: usize,
    pub tol: Float,
    pub learning_rate: Option<Float>,
    pub random_state: Option<u64>,
}

Stochastic Average Gradient (SAG) optimizer

Fields

max_epochs: usize

Maximum number of epochs

tol: Float

Convergence tolerance

learning_rate: Option<Float>

Learning rate

random_state: Option<u64>

Random seed

Implementations

impl SagOptimizer

pub fn minimize<F, G>( &self, _f_i: F, grad_f_i: G, x0: Array1<Float>, n_samples: usize, ) -> Result<Array1<Float>, String>

where F: Fn(&Array1<Float>, usize) -> Float, G: Fn(&Array1<Float>, usize) -> Array1<Float>,

Minimize using SAG for finite-sum problems f_i: individual loss function for sample i grad_f_i: gradient of individual loss function

Trait Implementations

impl Default for SagOptimizer

fn default() -> Self

Returns the “default value” for a type.