Class GaussianNoise

Apply additive zero-centered Gaussian noise. This is useful to mitigate overfitting(you could see it as a form of random data augmentation). Gaussian Noise(GS) is a natural choice as corruption process for real valued inputs. As it is a regularization layer, it is only active at training time.

Inheritance

System.Object

Keras

Base

BaseLayer

GaussianNoise

Implements

System.IDisposable

Inherited Members

BaseLayer.Set(BaseLayer[])

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.Layers

Assembly: Keras.dll

Syntax

public class GaussianNoise : BaseLayer, IDisposable

Constructors

GaussianNoise(Single)

Initializes a new instance of the GaussianNoise class.

Declaration

public GaussianNoise(float stddev)

Parameters

Type	Name	Description
System.Single	stddev	float, standard deviation of the noise distribution.

Implements

System.IDisposable