The UserAccuracy function method returns a user accuracy value. The result is an array with one value per class.

User accuracy is the probability that a value predicted to be in a certain class really is that class. The probability is based on the fraction of correctly predicted values to the total number of values predicted to be in a class.

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

Asphalt: 2385 / 2394 = 0.996

Concrete: 332 / 333 = 0.997

Grass: 908 / 917 = 0.99

Tree: 1084 / 1093 = 0.992

Building: 2053 / 2071 = 0.991

Example


The code example below evaluates classifications using a confusion matrix.

PRO EvaluateClassificationUsingConfusionMatrix
    COMPILE_OPT IDL2
 
    ; Start the application
    e = ENVI()
 
    ; Open an input file
    File = Filepath('qb_boulder_msi', Subdir=['data'], $
    Root_Dir=e.Root_Dir)
    Raster = e.OpenRaster(File)
    File2 = Filepath('qb_boulder_roi.xml', Subdir=['data'], $
    Root_Dir=e.Root_Dir)
    Rois = envi.OpenROI(roiFile)
 
    ; Get training statistics
    StatTask = ENVITask('ROIStatistics')
    StatTask.INPUT_RASTER = Raster
    StatTask.INPUT_ROI = Rois
    StatTask.Execute
 
    ; Get the task from the catalog of ENVITasks
    Task = ENVITask('MahalanobisDistanceClassification')
 
    ; Define inputs
    Task.INPUT_RASTER = Raster
    Task.COVARIANCE = StatTask.Covariance
    Task.MEAN = StatTask.Mean
    Task.CLASS_PIXEL_COUNT = StatTask.Roi_Pixel_Count
    Task.CLASS_NAMES = [Rois[0].name, Rois[1].name, Rois[2].name]
    Task.CLASS_COLORS = [[0,0,255], [0,255,0], [255,0,0]]
 
    ; Run the task and display the result
    Task.Execute
    ClassRaster = Task.OUTPUT_RASTER
    View = e.GetView()
    Layer = View.CreateLayer(ClassRaster)
 
    ; Add the output to the Data Manager
    envi.Data.Add, ClassRaster
 
    ; Calculate the confusion matrix
    ConfusionMatrix = ENVICalculateConfusionMatrixFromRaster(ClassRaster, Rois)
 
    ; Print results
    Print, 'Confusion Matrix:'
    Print, ConfusionMatrix.Confusion_Matrix
    Print, 'Errors of commission: '
    Print, Transpose([[ConfusionMatrix.Column_Names+': '], [(ConfusionMatrix.CommissionError()).ToString()]])
    Print, 'Errors of omission: '
    Print, Transpose([[ConfusionMatrix.Column_Names+': '], [(ConfusionMatrix.OmissionError()).ToString()]])
    Print, 'Overall accuracy: ', ConfusionMatrix.Accuracy()
END

Syntax


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

Return Value


This function method returns the user accuracy value from the confusion matrix.

Arguments


None

Keywords


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

Introduced

API Version


4.3

See Also


ENVIConfusionMatrix