ILossFunction (ai.ml 0.0.1 API)

Type Parameters:

Y - The domain of elements to measure the loss for.

All Known Subinterfaces:

IBatchLossFunction<Y>, IClassificationLossFunction, IMultiLabelClassificationLossFunction, IRankingLossFunction, ISingleLabelClassificationBatchLossFunction
```
public interface ILossFunction<Y>
```
A loss function is defined for a domain quantizing the error of an elment in a domain D compared to the ground truth. The function in general has the signature: L: D \times D \rightarrow \R, where D is the considered domain and \R represents the reals. Usually a loss function is normalized to take values from the unit interval [0,1].

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`double`	`loss(Y expected, Y actual)`	Computes and returns the loss for the given element with respect to the ground truth value.

- Method Detail
  - loss
```
double loss(Y expected,
            Y actual)
```
    Computes and returns the loss for the given element with respect to the ground truth value.
    
    Parameters:
    
    expected - The ground truth value to compare the given element to.
    
    actual - The element to compare to the expected value.
    
    Returns:
    
    The loss for the given element with respect to the ground truth value.