Click or drag to resize
Accord.NET (logo)

ILossT Interface

Common interface for loss functions, such as SquareLoss, HingeLoss and CategoryCrossEntropyLoss.

Namespace:  Accord.Math.Optimization.Losses
Assembly:  Accord.Math (in Accord.Math.dll) Version: 3.8.0
public interface ILoss<T> : ILoss<T, double>
Request Example View Source

Type Parameters

The type for the expected data.

The ILossT type exposes the following members.

Public methodLoss
Computes the loss between the expected values (ground truth) and the given actual values that have been predicted.
(Inherited from ILossTScore, TLoss.)

In mathematical optimization, statistics, decision theory and machine learning, a loss function or cost function is a function that maps an event or values of one or more variables onto a real number intuitively representing some "cost" associated with the event. An optimization problem seeks to minimize a loss function. An objective function is either a loss function or its negative (sometimes called a reward function, a profit function, a utility function, a fitness function, etc.), in which case it is to be maximized.


See Also