SAGA 9.4.2 | Tool Library Documentation

Random Forest Presence Prediction (ViGrA)


Description

Random Forest Presence Prediction


References


Parameters

 NameTypeIdentifierDescriptionConstraints
InputFeaturesgrid list, inputFEATURES--
Presence Datashapes, inputPRESENCE--
OutputPresence Predictiongrid, outputPREDICTION--
Presence Probabilitygrid, output, optionalPROBABILITY--
OptionsGrid Systemgrid systemPARAMETERS_GRID_SYSTEM--
Background Sample Density [Percent]floating point numberBACKGROUND-Minimum: 0.000000 Maximum: 100.000000 Default: 1.000000
Minimum Redundancy Feature SelectionbooleanDO_MRMRUse only features selected by the minimum Redundancy Maximum Relevance (mRMR) algorithmDefault: 0
Number of Featuresinteger numbermRMR_NFEATURES-Minimum: 1 Default: 50
DiscretizationbooleanmRMR_DISCRETIZEuncheck this means no discretizaton (i.e. data is already integer)Default: 1
Discretization Thresholdfloating point numbermRMR_THRESHOLDa double number of the discretization threshold; set to 0 to make binarizationMinimum: 0.000000 Default: 1.000000
Selection MethodchoicemRMR_METHOD-Available Choices: [0] Mutual Information Difference (MID) [1] Mutual Information Quotient (MIQ) Default: 0
Tree Countinteger numberRF_TREE_COUNTHow many trees to create?Minimum: 1 Default: 32
Samples per Treefloating point numberRF_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 Sizeinteger numberRF_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

Command Line


Usage: saga_cmd imagery_vigra 10 [-FEATURES ] [-PREDICTION ] [-PROBABILITY ] [-PRESENCE ] [-BACKGROUND ] [-DO_MRMR ] [-mRMR_NFEATURES ] [-mRMR_DISCRETIZE ] [-mRMR_THRESHOLD ] [-mRMR_METHOD ] [-RF_TREE_COUNT ] [-RF_TREE_SAMPLES ] [-RF_REPLACE ] [-RF_SPLIT_MIN_SIZE ] [-RF_NODE_FEATURES ] [-RF_STRATIFICATION ]
  -FEATURES:          	Features
	grid list, input
  -PREDICTION:        	Presence Prediction
	grid, output
  -PROBABILITY:       	Presence Probability
	grid, output, optional
  -PRESENCE:          	Presence Data
	shapes, input
  -BACKGROUND:     	Background Sample Density [Percent]
	floating point number
	Minimum: 0.000000
	Maximum: 100.000000
	Default: 1.000000
  -DO_MRMR:           	Minimum Redundancy Feature Selection
	boolean
	Default: 0
  -mRMR_NFEATURES:    	Number of Features
	integer number
	Minimum: 1
	Default: 50
  -mRMR_DISCRETIZE:   	Discretization
	boolean
	Default: 1
  -mRMR_THRESHOLD: 	Discretization Threshold
	floating point number
	Minimum: 0.000000
	Default: 1.000000
  -mRMR_METHOD:       	Selection Method
	choice
	Available Choices:
	[0] Mutual Information Difference (MID)
	[1] Mutual Information Quotient (MIQ)
	Default: 0
  -RF_TREE_COUNT:     	Tree Count
	integer number
	Minimum: 1
	Default: 32
  -RF_TREE_SAMPLES:	Samples per Tree
	floating point number
	Minimum: 0.000000
	Maximum: 1.000000
	Default: 1.000000
  -RF_REPLACE:        	Sample with Replacement
	boolean
	Default: 1
  -RF_SPLIT_MIN_SIZE: 	Minimum Node Split Size
	integer number
	Minimum: 1
	Default: 1
  -RF_NODE_FEATURES:  	Features per Node
	choice
	Available Choices:
	[0] logarithmic
	[1] square root
	[2] all
	Default: 1
  -RF_STRATIFICATION: 	Stratification
	choice
	Available Choices:
	[0] none
	[1] equal
	[2] proportional
	Default: 0