optimizer_sgd: Stochastic Gradient Descent Optimizer

In metANN: Metaheuristic and Gradient-Based Optimization for Neural Network Training and Continuous Problems

Stochastic Gradient Descent Optimizer

Description

Creates a stochastic gradient descent optimizer object.

Usage

optimizer_sgd(learning_rate = 0.01, epochs = 100, batch_size = NULL)

Arguments

learning_rate	Learning rate.
epochs	Number of training epochs.
batch_size	Mini-batch size. If NULL, full-batch training is used.

Value

An object of class "met_optimizer".

References

Robbins, H., and Monro, S. (1951). A Stochastic Approximation Method. The Annals of Mathematical Statistics, 22(3), 400–407. doi:10.1214/aoms/1177729586

Examples

optimizer_sgd()

metANN documentation built on May 16, 2026, 1:06 a.m.