Performance (Costs)

Synopsis

This operator provides the ability to evaluate misclassification costs for performance evaluation of classification tasks.

Description

The Performance (Costs) operator provides the ability to evaluate misclassification costs. A cost matrix should be specified through thecost matrixparameter. The cost matrix is similar in structure to a confusion matrix because it has predicted classes in one dimension and actual classes on the other dimension. Therefore the cost matrix can denote the costs for every possible classification outcome: predicted label vs. actual label. Actually this matrix is a matrix of misclassification costs because you can specify different weights for certain classes misclassified as other classes. Weights can also be assigned to correct classifications but they are not taken into account for evaluating misclassification costs. The classes in the matrix are labeled as Class 1, Class 2 etc where classes are numbered according to their order in the internal mapping. Theclass order definitionparameter allows you to specify the class order for the matrix in which case classes are ordered according to the order specified in this parameter (instead of internal mappings). For a better understanding of this operator please study the attached Example Process.

Input

example set

This input port expects a labeled ExampleSet. The Apply Model operator is a good example of such operators that provide labeled data. Make sure that the ExampleSet haslabelandpredictionattributes. Please see the Set Role operator for more details about attribute roles.

Output

example set

The ExampleSet that was given as input is passed without changing to the output through this port. This is usually used to reuse the same ExampleSet in further operators or to view the ExampleSet in the Results Workspace.

performance

This port delivers a Performance Vector which has information about the misclassification costs.

Parameters

Cost matrix

This parameter is used for specifying the cost matrix. The cost matrix is similar in structure to a confusion matrix because it has predicted classes in one dimension and actual classes on the other dimension. Therefore the cost matrix can denote the costs for every possible classification outcome: predicted label vs. actual label. Actually this matrix is a matrix of misclassification costs because you can specify different weights for certain classes misclassified as other classes. Weights can also be assigned to correct classifications but they are not taken into account for evaluating misclassification costs. The classes in the matrix are labeled as Class 1, Class 2 etc where classes are numbered according to their order in the internal mapping. Theclass order definitionparameter can be used for specifying the class order for the matrix (instead of internal mappings).

类排序r definition

Theclass order definitionparameter allows you to specify the class order for the cost matrix in which case classes are ordered according to the order specified in this parameter (instead of internal mappings).