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This function takes in truth examples, truth class values, and a classifier. It uses the classifier and truth examples (ignoring the class values) to calculate predicted class values. Then it computes a confusion matrix and accuracy metrics between the truth and predicted class values. For descriptions of examples and class values, see Prepare Data for Classification.

The following diagrams show typical workflows where this function is used:



See the following topics for code examples:


Result = ENVIEvaluateClassifier(Input_Examples, Input_Classifier [, Keywords=value])

Return Value

This function returns a reference to an ENVIConfusionMatrix object.



Specify an input ENVIExamples object.


Specify an ENVISoftmaxRegressionClassifier or ENVISVMClassifier object.


ERROR (optional)

Set this keyword to a named variable that will contain any error message issued during execution of this routine. If no error occurs, the ERROR variable will be set to a null string (''). If an error occurs and the routine is a function, then the function result will be undefined.

When this keyword is not set and an error occurs, ENVI returns to the caller and execution halts. In this case, the error message is contained within !ERROR_STATE and can be caught using IDL's CATCH routine. See IDL Help for more information on !ERROR_STATE and CATCH.

See Manage Errors for more information on error handling in ENVI programming.

Version History

ENVI 5.4


API Version


See Also

ENVIEvaluateClassifierTask, ENVIConfusionMatrix, ENVIExamples, ENVISoftmaxRegressionClassifier, ENVIRestoreObject

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