The Machine Learning Evaluate Classifier tool evaluates a classifier using labeled rasters that may or may not have been used during training. It generates a report containing statistics about the classifiers performance against the input rasters, and provides a confusion matrix of all classes as part of the report.

You can also write a script to evaluate a classifier using the MachineLearningEvaluateClassifier task.

  1. From the Toolbox, select Machine Learning > Machine Learning Evaluate Classifier. The Machine Learning Evaluate Classifier dialog appears.
  2. Add one or more Machine Learning labeled rasters to the Input Rasters field, then click OK.
  3. In the Input Model field, select a trained machine learning model to evaluate with the input rasters.

  4. In the Output Report field, enter a location and filename for the report.

  5. To reuse these task settings in future ENVI sessions, save them to a file. Click the down arrow and select Save Parameter Values, then specify the location and filename to save to. Note that some parameter types, such as rasters, vectors, and ROIs, will not be saved with the file. To apply the saved task settings, click the down arrow and select Restore Parameter Values, then select the file where you previously stored your settings.

  6. To run the process on a local or remote ENVI Server, click the down arrow and select Run Task in the Background or Run Task on remote ENVI Server name. The ENVI Server Job Console will show the progress of the job and will provide a link to display the result when processing is complete. See the ENVI Servers topic in ENVI Help for more information.

  7. Click OK.

See Also

Machine Learning Labeling Tool