Class Adagrad

Adagrad is an optimizer with parameter-specific learning rates, which are adapted relative to how frequently a parameter gets updated during training. The more updates a parameter receives, the smaller the learning rate.

Inheritance

System.Object

Keras

Base

Adagrad

Implements

System.IDisposable

Inherited Members

Base.Parameters

Base.None

Base.Init()

Base.ToPython()

Base.InvokeStaticMethod(Object, String, Dictionary<String, Object>)

Base.InvokeMethod(String, Dictionary<String, Object>)

Base.Item[String]

Keras.Instance

Keras.keras

Keras.keras2onnx

Keras.tfjs

Keras.Dispose()

Keras.ToTuple(Array)

Keras.ToList(Array)

System.Object.Equals(System.Object)

System.Object.Equals(System.Object, System.Object)

System.Object.GetHashCode()

System.Object.GetType()

System.Object.MemberwiseClone()

System.Object.ReferenceEquals(System.Object, System.Object)

System.Object.ToString()

Namespace: Keras.Optimizers

Assembly: Keras.dll

Syntax

public class Adagrad : Base, IDisposable

Constructors

Adagrad(Single, Nullable<Single>, Single)

Initializes a new instance of the Adagrad class.

Declaration

public Adagrad(float lr = 0.01F, float? epsilon = default(float? ), float decay = 0F)

Parameters

Type	Name	Description
System.Single	lr	float >= 0. Initial learning rate.
System.Nullable<System.Single>	epsilon	float >= 0. If None, defaults to K.epsilon().
System.Single	decay	float >= 0. Learning rate decay over each update..

Implements

System.IDisposable