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ILossTScore, TLoss Interface

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

Namespace:  Accord.Math.Optimization.Losses
Assembly:  Accord.Math (in Accord.Math.dll) Version: 3.8.0
public interface ILoss<TScore, TLoss>
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Type Parameters

The type for the predicted score values.
The type for the loss value. Default is double.

The ILossTScore, TLoss 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.

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.


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