TrainLinearSVM Task

This task divides a dataset into a number of classes in order to find a maximum marginal hyperplane.

For background on the algorithm used, see Linear SVM Classification.

Example

; Start the application

e = ENVI()

; Open an input raster file

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

  Root_Dir=e.Root_Dir)

Raster = e.OpenRaster(RasterFile)

; Open an input ROI file

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

Root_Dir=e.Root_Dir)

ROI = e.OpenROI(ROIFile)

; Get the statistics task from the catalog of ENVITasks

StatsTask = ENVITask('NormalizationStatistics')

; Define inputs

StatsTask.INPUT_RASTERS = Raster

; Run the task

StatsTask.Execute

; Get the data prep task from the catalog of ENVITasks

DataPrepTask = ENVITask('MLTrainingDataFromROIs')

; Define inputs

DataPrepTask.INPUT_RASTER = Raster

DataPrepTask.INPUT_ROI = ROI

DataPrepTask.BACKGROUND_LABELS = ['Bright Roof', 'Water']

DataPrepTask.NORMALIZE_MIN_MAX = StatsTask.Normalization

DataPrepTask.Execute

; Get the training task from the catalog of ENVITasks

TrainTask = ENVITask('TrainLinearSVM')

; Define inputs

TrainTask.INPUT_RASTER = DataPrepTask.OUTPUT_RASTER

; Run the task

TrainTask.Execute

; Output model metadata

outputModelUri = TrainTask.OUTPUT_MODEL_URI

print, 'Model URI: ' + outputModelUri

outputModel = TrainTask.OUTPUT_MODEL

print, outputModel.Attributes, /IMPLIED

Syntax

Result = ENVITask('TrainLinearSVM')

Input properties (Set, Get): BALANCE_CLASSES, INPUT_RASTERS, MODEL_NAME, MODEL_DESCRIPTION, OUTPUT_MODEL_URI

Output properties (Get only): OUTPUT_MODEL

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

Methods

This task inherits the following methods from ENVITask. See the ENVITask topic in ENVI Help.

AddParameter
Execute
Parameter
ParameterNames
RemoveParameters

Properties

This task inherits the following properties from ENVITask:

COMMUTE_ON_DOWNSAMPLE

COMMUTE_ON_SUBSET

DESCRIPTION

DISPLAY_NAME

NAME

REVISION

See the ENVITask topic in ENVI Help for details.

This task also contains the following properties:

BALANCE_CLASSES (optional)

Specify whether all classes should be considered equal during training. This helps to account for classes with few samples compared to classes with many samples.

INPUT_RASTERS (required)

Specify one or more preprocessed training rasters to be used for training.

MODEL_NAME (optional)

Specify the name of the model. The default is Linear SVM Supervised Classifier.

MODEL_DESCRIPTION (optional)

Specify the purpose of the model.

OUTPUT_MODEL (required)

This is a reference to the output model file.

OUTPUT_MODEL_URI (optional)

Specify a string with the fully qualified filename and path of the associated OUTPUT_MODEL. If you do not specify this property, or set it to an exclamation symbol (!), a temporary file will be created.

Version History

Deep Learning 2.0

Introduced