The Accuracy function method returns the overall accuracy of a confusion matrix.

The overall accuracy is calculated by summing the number of correctly classified values and dividing by the total number of values. The correctly classified values are located along the upper-left to lower-right diagonal of the confusion matrix. The total number of values is the number of values in either the truth or predicted-value arrays.

In the example confusion matrix, the overall accuracy is computed as follows:

Correctly classified values: 2385 + 332 + 908 + 1084 + 2053 = 6762

Total number of values: 6808

Overall accuracy: 6762 / 6808 = 0.993243

Example

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See the following topics for code examples:

• Code Example: Support Vector Machine Classification Using API Objects
• Code Example: Softmax Regression Classification Using API Objects
• Evaluate the Classifier

Syntax

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Result = ENVIConfusionMatrix.Accuracy([, ERROR=variable])

Return Value

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This function method returns the overall accuracy from a confusion matrix.

Arguments

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None

Keywords

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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

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ENVI 5.4

Introduced

API Version

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3.8

See Also

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ENVIConfusionMatrix