SAGA-GIS Tool Library Documentation (v9.1.2)

Tool Support Vector Machine Classification

Integration of the OpenCV Machine Learning library for Support Vector Machine classification of gridded features.


References


Parameters

 NameTypeIdentifierDescriptionConstraints
InputFeaturesGrid list, inputFEATURES--
Training SamplesTable, inputTRAIN_SAMPLESProvide a class identifier in the first field followed by sample data corresponding to the input feature grids.-
Training AreasShapes, inputTRAIN_AREAS--
OutputClassificationGrid, outputCLASSES--
Look-up Table (*)Table, output, optionalCLASSES_LUTA reference list of the grid values that have been assigned to the training classes.-
OptionsGrid SystemGrid systemPARAMETERS_GRID_SYSTEM--
NormalizeBooleanNORMALIZE-Default: 0
Colors from FeaturesBoolean, GUIRGB_COLORSUse the first three features in list to obtain blue, green, red components for class colour in look-up table.Default: 0
TrainingChoiceMODEL_TRAIN-Available Choices:
[0] training areas
[1] training samples
[2] load from file
Default: 0
Class IdentifierTable fieldTRAIN_CLASS--
Buffer SizeFloating pointTRAIN_BUFFERFor non-polygon type training areas, creates a buffer with a diameter of specified size.Minimum: 0.000000
Default: 1.000000
Load ModelFile pathMODEL_LOADUse a model previously stored to file.-
Save ModelFile pathMODEL_SAVEStores model to file to be used for subsequent classifications instead of training areas.-
SVM TypeChoiceSVM_TYPE-Available Choices:
[0] c-support vector classification
[1] nu support vector classification
[2] distribution estimation (one class)
[3] epsilon support vector regression
[4] nu support vector regression
Default: 0
CFloating pointC-Minimum: 0.000000
Default: 5.000000
NuFloating pointNU-Minimum: 0.000000
Default: 0.500000
PFloating pointP-Minimum: 0.000000
Default: 0.500000
Kernel TypeChoiceKERNEL-Available Choices:
[0] linear
[1] polynomial
[2] radial basis function
[3] sigmoid
[4] exponential chi2
[5] histogram intersection
Default: 2
Coefficient 0Floating pointCOEF0-Minimum: 0.000000
Default: 1.000000
DegreeFloating pointDEGREE-Minimum: 0.000000
Default: 0.500000
GammaFloating pointGAMMA-Minimum: 0.000000
Default: 5.000000
(*) optional

Command-line

Usage: saga_cmd imagery_opencv 7 [-FEATURES <str>] [-NORMALIZE <str>] [-CLASSES <str>] [-CLASSES_LUT <str>] [-MODEL_TRAIN <str>] [-TRAIN_SAMPLES <str>] [-TRAIN_AREAS <str>] [-TRAIN_CLASS <str>] [-TRAIN_BUFFER <double>] [-MODEL_LOAD <str>] [-MODEL_SAVE <str>] [-SVM_TYPE <str>] [-C <double>] [-NU <double>] [-P <double>] [-KERNEL <str>] [-COEF0 <double>] [-DEGREE <double>] [-GAMMA <double>]
  -FEATURES:<str>       	Features
	Grid list, input
  -NORMALIZE:<str>      	Normalize
	Boolean
	Default: 0
  -CLASSES:<str>        	Classification
	Grid, output
  -CLASSES_LUT:<str>    	Look-up Table
	Table, output, optional
  -MODEL_TRAIN:<str>    	Training
	Choice
	Available Choices:
	[0] training areas
	[1] training samples
	[2] load from file
	Default: 0
  -TRAIN_SAMPLES:<str>  	Training Samples
	Table, input
  -TRAIN_AREAS:<str>    	Training Areas
	Shapes, input
  -TRAIN_CLASS:<str>    	Class Identifier
	Table field
  -TRAIN_BUFFER:<double>	Buffer Size
	Floating point
	Minimum: 0.000000
	Default: 1.000000
  -MODEL_LOAD:<str>     	Load Model
	File path
  -MODEL_SAVE:<str>     	Save Model
	File path
  -SVM_TYPE:<str>       	SVM Type
	Choice
	Available Choices:
	[0] c-support vector classification
	[1] nu support vector classification
	[2] distribution estimation (one class)
	[3] epsilon support vector regression
	[4] nu support vector regression
	Default: 0
  -C:<double>           	C
	Floating point
	Minimum: 0.000000
	Default: 5.000000
  -NU:<double>          	Nu
	Floating point
	Minimum: 0.000000
	Default: 0.500000
  -P:<double>           	P
	Floating point
	Minimum: 0.000000
	Default: 0.500000
  -KERNEL:<str>         	Kernel Type
	Choice
	Available Choices:
	[0] linear
	[1] polynomial
	[2] radial basis function
	[3] sigmoid
	[4] exponential chi2
	[5] histogram intersection
	Default: 2
  -COEF0:<double>       	Coefficient 0
	Floating point
	Minimum: 0.000000
	Default: 1.000000
  -DEGREE:<double>      	Degree
	Floating point
	Minimum: 0.000000
	Default: 0.500000
  -GAMMA:<double>       	Gamma
	Floating point
	Minimum: 0.000000
	Default: 5.000000