Tool Random Forest Classification (ViGrA)
Random Forest Classification.
References
- Author: O.Conrad (c) 2013
- Menu: Imagery|Classification|Machine Learning
Parameters
Name | Type | Identifier | Description | Constraints | |
---|---|---|---|---|---|
Input | Features | Grid list, input | FEATURES | - | - |
Training Areas | Shapes, input | TRAINING | - | - | |
Output | Random Forest Classification | Grid, output | CLASSES | - | - |
Prediction Probability (*) | Grid, output, optional | PROBABILITY | - | - | |
Feature Probabilities | Grid list, output | PROBABILITIES | - | - | |
Feature Importances | Table, output | IMPORTANCES | - | - | |
Options | Grid System | Grid system | PARAMETERS_GRID_SYSTEM | - | - |
Feature Probabilities | Boolean | BPROBABILITIES | - | Default: 0 | |
Label Field | Table field | FIELD | - | - | |
Use Label as Identifier | Boolean | LABEL_AS_ID | Use training area labels as identifier in classification result, assumes all label values are integer numbers! | Default: 0 | |
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 | |
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 9 [-FEATURES <str>] [-CLASSES <str>] [-PROBABILITY <str>] [-BPROBABILITIES <str>] [-PROBABILITIES <str>] [-IMPORTANCES <str>] [-TRAINING <str>] [-FIELD <str>] [-LABEL_AS_ID <str>] [-DO_MRMR <str>] [-mRMR_NFEATURES <num>] [-mRMR_DISCRETIZE <str>] [-mRMR_THRESHOLD <double>] [-mRMR_METHOD <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 -CLASSES:<str> Random Forest Classification Grid, output -PROBABILITY:<str> Prediction Probability Grid, output, optional -BPROBABILITIES:<str> Feature Probabilities Boolean Default: 0 -PROBABILITIES:<str> Feature Probabilities Grid list, output -IMPORTANCES:<str> Feature Importances Table, output -TRAINING:<str> Training Areas Shapes, input -FIELD:<str> Label Field Table field -LABEL_AS_ID:<str> Use Label as Identifier Boolean Default: 0 -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_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