Tool Random Forest Presence Prediction (ViGrA)

Random Forest Presence Prediction

References

ViGrA - Vision with Generic Algorithms

Author: O.Conrad (c) 2015
Menu: Grid|Analysis|Macroecology

Parameters

	Name	Type	Identifier	Description	Constraints
Input	Features	Grid list, input	`FEATURES`	-	-
Input	Presence Data	Shapes, input	`PRESENCE`	-	-
Output	Presence Prediction	Grid, output	`PREDICTION`	-	-
Output	Presence Probability (*)	Grid, output, optional	`PROBABILITY`	-	-
Options	Grid System	Grid system	`PARAMETERS_GRID_SYSTEM`	-	-
	Background Sample Density [Percent]	Floating point	`BACKGROUND`	-	Minimum: 0.000000 Maximum: 100.000000 Default: 1.000000
	Minimum Redundancy Feature Selection	Boolean	`DO_MRMR`	Use only features selected by the minimum Redundancy Maximum Relevance (mRMR) algorithm	Default: 0
	Number of Features	Integer	`mRMR_NFEATURES`	-	Minimum: 1 Default: 50
	Discretization	Boolean	`mRMR_DISCRETIZE`	uncheck this means no discretizaton (i.e. data is already integer)	Default: 1
	Discretization Threshold	Floating point	`mRMR_THRESHOLD`	a double number of the discretization threshold; set to 0 to make binarization	Minimum: 0.000000 Default: 1.000000
	Selection Method	Choice	`mRMR_METHOD`	-	Available Choices: [0] Mutual Information Difference (MID) [1] Mutual Information Quotient (MIQ) Default: 0
	Load Model	File path	`RF_IMPORT`	-	-
	Save Model	File path	`RF_EXPORT`	-	-
	Tree Count	Integer	`RF_TREE_COUNT`	How many trees to create?	Minimum: 1 Default: 32
	Samples per Tree	Floating point	`RF_TREE_SAMPLES`	Specifies the fraction of the total number of samples used per tree for learning.	Minimum: 0.000000 Maximum: 1.000000 Default: 1.000000
	Sample with Replacement	Boolean	`RF_REPLACE`	Sample from training population with or without replacement?	Default: 1
	Minimum Node Split Size	Integer	`RF_SPLIT_MIN_SIZE`	Number of examples required for a node to be split. Choose 1 for complete growing.	Minimum: 1 Default: 1
	Features per Node	Choice	`RF_NODE_FEATURES`	-	Available Choices: [0] logarithmic [1] square root [2] all Default: 1
	Stratification	Choice	`RF_STRATIFICATION`	Specifies 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 10 [-FEATURES <str>] [-PREDICTION <str>] [-PROBABILITY <str>] [-PRESENCE <str>] [-BACKGROUND <double>] [-DO_MRMR <str>] [-mRMR_NFEATURES <num>] [-mRMR_DISCRETIZE <str>] [-mRMR_THRESHOLD <double>] [-mRMR_METHOD <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>]
  -FEATURES:<str>          	Features
	Grid list, input
  -PREDICTION:<str>        	Presence Prediction
	Grid, output
  -PROBABILITY:<str>       	Presence Probability
	Grid, output, optional
  -PRESENCE:<str>          	Presence Data
	Shapes, input
  -BACKGROUND:<double>     	Background Sample Density [Percent]
	Floating point
	Minimum: 0.000000
	Maximum: 100.000000
	Default: 1.000000
  -DO_MRMR:<str>           	Minimum Redundancy Feature Selection
	Boolean
	Default: 0
  -mRMR_NFEATURES:<num>    	Number of Features
	Integer
	Minimum: 1
	Default: 50
  -mRMR_DISCRETIZE:<str>   	Discretization
	Boolean
	Default: 1
  -mRMR_THRESHOLD:<double> 	Discretization Threshold
	Floating point
	Minimum: 0.000000
	Default: 1.000000
  -mRMR_METHOD:<str>       	Selection Method
	Choice
	Available Choices:
	[0] Mutual Information Difference (MID)
	[1] Mutual Information Quotient (MIQ)
	Default: 0
  -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