Adagrad class

Implements the Adagrad optimization algorithm. Adapts the learning rate individually for each parameter based on the accumulated history of squared gradients.

Inheritance

• Object
• Optimizer
• Adagrad

Constructors

Adagrad(List<Tensor> parameters, {required double learningRate, double epsilon = 1e-8})

Creates an Adagrad optimizer for parameters with the specified learningRate and epsilon.

Properties

epsilon ↔ double

Small constant added to the denominator to prevent division by zero.

getter/setter pair

hashCode → int

The hash code for this object.

no setter, inherited

learningRate ↔ double

The step size factor applied during parameter updates.

getter/setter pair, inherited

parameters ↔ List<Tensor>

The collection of trainable parameter tensors managed by this optimizer.

getter/setter pair, inherited

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

Methods

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

step() → void

Performs a single optimization step, accumulating squared gradients and updating parameter values.

override

toString() → String

A string representation of this object.

inherited

zeroGrad() → void

Clears gradients by resetting the gradient buffer of every managed tensor in parameters to 0.0.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited