Class EarlyStopping

Stop training when a monitored quantity has stopped improving.

Inheritance

System.Object

Keras

Base

Callback

EarlyStopping

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.Callbacks

Assembly: Keras.dll

Syntax

public class EarlyStopping : Callback, IDisposable

Constructors

EarlyStopping(String, Single, Int32, Int32, String, Nullable<Single>, Boolean)

Initializes a new instance of the EarlyStopping class.

Declaration

public EarlyStopping(string monitor = "val_loss", float min_delta = 0F, int patience = 0, int verbose = 0, string mode = "auto", float? baseline = default(float? ), bool restore_best_weights = false)

Parameters

Type	Name	Description
System.String	monitor	quantity to be monitored.
System.Single	min_delta	minimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.
System.Int32	patience	number of epochs with no improvement after which training will be stopped.
System.Int32	verbose	verbosity mode.
System.String	mode	one of {auto, min, max}. In min mode, training will stop when the quantity monitored has stopped decreasing; in max mode it will stop when the quantity monitored has stopped increasing; in auto mode, the direction is automatically inferred from the name of the monitored quantity.
System.Nullable<System.Single>	baseline	Baseline value for the monitored quantity to reach. Training will stop if the model doesn't show improvement over the baseline.
System.Boolean	restore_best_weights	whether to restore model weights from the epoch with the best value of the monitored quantity. If False, the model weights obtained at the last step of training are used.

Implements

System.IDisposable