SAGA-GIS Tool Library Documentation (v7.8.2)

Tool Random Forest Table Classification (ViGrA)

Random Forest Table Classification.


References


Parameters

 NameTypeIdentifierDescriptionConstraints
InputTableTable, inputTABLETable with features, must include class-ID-
OutputFeature ImportancesTable, outputIMPORTANCES--
OptionsFeaturesTable fieldsFEATURESSelect features (table fields) for classification-
Prediction (*)Table fieldPREDICTIONThis is field that will have the prediction results. If not set it will be added to the table.-
TrainingTable fieldTRAININGthis is the table field that defines the training classes-
Use Label as IdentifierBooleanLABEL_AS_IDUse training area labels as identifier in classification result, assumes all label values are integer numbers!Default: 0
Load ModelFile pathRF_IMPORT--
Save ModelFile pathRF_EXPORT--
Tree CountIntegerRF_TREE_COUNTHow many trees to create?Minimum: 1
Default: 32
Samples per TreeFloating pointRF_TREE_SAMPLESSpecifies the fraction of the total number of samples used per tree for learning.Minimum: 0.000000
Maximum: 1.000000
Default: 1.000000
Sample with ReplacementBooleanRF_REPLACESample from training population with or without replacement?Default: 1
Minimum Node Split SizeIntegerRF_SPLIT_MIN_SIZENumber of examples required for a node to be split. Choose 1 for complete growing.Minimum: 1
Default: 1
Features per NodeChoiceRF_NODE_FEATURES-Available Choices:
[0] logarithmic
[1] square root
[2] all
Default: 1
StratificationChoiceRF_STRATIFICATIONSpecifies stratification strategy. Either none, equal amount of class samples, or proportional to fraction of class samples.Available Choices:
[0] none
[1] equal
[2] proportional
Default: 0
(*) optional

Command-line

Usage: saga_cmd imagery_vigra 11 [-TABLE <str>] [-FEATURES <str>] [-PREDICTION <str>] [-TRAINING <str>] [-LABEL_AS_ID <str>] [-IMPORTANCES <str>] [-RF_IMPORT <str>] [-RF_EXPORT <str>] [-RF_TREE_COUNT <num>] [-RF_TREE_SAMPLES <double>] [-RF_REPLACE <str>] [-RF_SPLIT_MIN_SIZE <num>] [-RF_NODE_FEATURES <str>] [-RF_STRATIFICATION <str>]
  -TABLE:<str>             	Table
	Table, input
  -FEATURES:<str>          	Features
	Table fields
  -PREDICTION:<str>        	Prediction
	Table field
  -TRAINING:<str>          	Training
	Table field
  -LABEL_AS_ID:<str>       	Use Label as Identifier
	Boolean
	Default: 0
  -IMPORTANCES:<str>       	Feature Importances
	Table, output
  -RF_IMPORT:<str>         	Load Model
	File path
  -RF_EXPORT:<str>         	Save Model
	File path
  -RF_TREE_COUNT:<num>     	Tree Count
	Integer
	Minimum: 1
	Default: 32
  -RF_TREE_SAMPLES:<double>	Samples per Tree
	Floating point
	Minimum: 0.000000
	Maximum: 1.000000
	Default: 1.000000
  -RF_REPLACE:<str>        	Sample with Replacement
	Boolean
	Default: 1
  -RF_SPLIT_MIN_SIZE:<num> 	Minimum Node Split Size
	Integer
	Minimum: 1
	Default: 1
  -RF_NODE_FEATURES:<str>  	Features per Node
	Choice
	Available Choices:
	[0] logarithmic
	[1] square root
	[2] all
	Default: 1
  -RF_STRATIFICATION:<str> 	Stratification
	Choice
	Available Choices:
	[0] none
	[1] equal
	[2] proportional
	Default: 0