MachineLearningEvaluateClassifier Task

This task 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.

Example

; Start the application

e = ENVI(/HEADLESS)

; Open an ROI file

File = Filepath('qb_boulder_roi.xml', Subdir=['data'], $

Root_Dir=e.Root_Dir)

ROI = ENVI.OpenROI(File)

; Open an input file

File = Filepath('qb_boulder_msi', Subdir=['data'], $

Root_Dir=e.Root_Dir)

Raster = e.OpenRaster(File)

; Specify an output report name

User = GetEnv('USERNAME')

Output_Report = ``

; Run statistics normalization

Task_1 = ENVITask('NormalizationStatistics')

Task_1.INPUT_RASTERS = Raster

Task_1.Execute

; Run the MLTrainingDataFromROIs task

Task_2 = ENVITask('MLTrainingDataFromROIs')

Task_2.INPUT_RASTER = Raster

Task_2.INPUT_ROI = ROI

Task_2.NORMALIZE_MIN_MAX = Task_1.normalization

Task_2.Execute

; Run the TrainRandomForest task

Task_3 = ENVITask('TrainRandomForest')

Task_3.INPUT_RASTERS = Task_2.output_raster

Task_3.Execute

; Run the MachineLearningClassification task

Task_4 = ENVITask('MachineLearningClassification')

Task_4.INPUT_RASTER = Raster

Task_4.INPUT_MODEL = Task_3.output_model

Task_4.NORMALIZE_MIN_MAX = Task_1.normalization

Task_4.Execute

; Run the task

Task_5 = ENVITask('MachineLearningEvaluateClassifier')

Task_5.INPUT_RASTERS = Task_2.output_raster

Task_5.INPUT_MODEL = Task_3.output_model

Task_5.OUTPUT_REPORT_URI = e.GetTemporaryFilename('.json', /CLEANUP_ON_EXIT)

Task_5.Execute

; Output the Machine Learning Evaluate Classifier result

print, Task_5.OUTPUT_REPORT, /IMPLIED_PRINT

Syntax

Result = ENVITask('MachineLearningEvaluateClassifier')

Input parameters (Set, Get): INPUT_RASTERS, INPUT_MODEL, OUT_REPORT_URI

Output parameters (Get only): OUTPUT_REPORT

Parameters marked as "Set" are those that you can set to specific values. You can also retrieve their current values any time. Parameters marked as "Get" are those whose values you can retrieve but not set.

Input Parameters

INPUT_RASTERS (required)

Specify the single row of spectral rasters that contain pixels for training.

INPUT_MODEL (required)

Specify a trained machine learning model to use for classifying the INPUT_RASTERS.

OUT_REPORT_URI (optional)

Specify the JSON URI containing the report. If not specified, a temporary URI will be used.

Output Parameters

OUTPUT_REPORT

Specify a hash object containing the results written to OUPUT_REPORT_URI.

Methods

Execute

Parameter

ParameterNames

See ENVI Help for details on these ENVITask methods.

Properties

DESCRIPTION

DISPLAY_NAME

NAME

REVISION

See the ENVITask topic in ENVI Help for details.

Version History

Machine Learning 3.0

Introduced