|  | ## Performance (Ranking)

#### Synopsis

This operator delivers as a performance value representing costs for the cofidence rank of the true label.

#### Description

This performance evaluator operator should be used for tasks, where it is not only important that the real class is assigned the highest but receives a comparably high confidence.

This operator will sort the confidences for each label and depending of the rank position of the real label, costs are generated. You can define these costs by the parameter ranking_costs. The costs are entered for hole intervalls, so you don't have to enter a cost value for each rank. These intervalls are defined by their start rank and range either until the start of the next interval or infinite. Everything before the first mentioned rank will receive costs of 0. The counting of rank starts by 0, so the most confident label is rank 0.

The costs are entered on the right side of the table.

For example, if you want to assing costs of zero if the true label is predicted with the highest confidence, 1 for the second place, 2 for the third and 10 for each following, you have to enter:

1 | 1
2 | 2
3 | 10

#### Input

- example set: expects: ExampleSet

#### Output

- example set:
- performance:

#### Parameters

- ranking costs: This parameter defines the costs when the real call isn't the one with the highest confidence.

#### ExampleProcess