Random Forest Presence Prediction (ViGrA)
imagery_vigra
ParameterMultipleInput|FEATURES|Features|3|False
OutputRaster|PREDICTION|Presence Prediction
OutputRaster|PROBABILITY|Presence Probability
ParameterVector|PRESENCE|Presence Data|-1|False
ParameterNumber|BACKGROUND|Background Sample Density [Percent]| 0.000000| 100.000000| 1.000000
ParameterBoolean|DO_MRMR|Minimum Redundancy Feature Selection|False
ParameterNumber|mRMR_NFEATURES|Number of Features| 1|None| 50
ParameterBoolean|mRMR_DISCRETIZE|Discretization|True
ParameterNumber|mRMR_THRESHOLD|Discretization Threshold| 0.000000|None| 1.000000
ParameterSelection|mRMR_METHOD|Selection Method|[0] Mutual Information Difference (MID);[1] Mutual Information Quotient (MIQ)| 0
ParameterFile|RF_IMPORT|Import from File|False|False
ParameterFile|RF_EXPORT|Export to File|False|False
ParameterNumber|RF_TREE_COUNT|Tree Count| 1|None| 32
ParameterNumber|RF_TREE_SAMPLES|Samples per Tree| 0.000000| 1.000000| 1.000000
ParameterBoolean|RF_REPLACE|Sample with Replacement|True
ParameterNumber|RF_SPLIT_MIN_SIZE|Minimum Node Split Size| 1|None| 1
ParameterSelection|RF_NODE_FEATURES|Features per Node|[0] logarithmic;[1] square root;[2] all| 1
ParameterSelection|RF_STRATIFICATION|Stratification|[0] none;[1] equal;[2] proportional| 0