Supervised Classification (Table Fields)
- Author: O.Conrad (c) 2012
- Menu: Table | Classification;Shapes | Attributes
Description
Standard classifiers for supervised classification based on attributes. Classifiers can be trained in three different ways:
- Known classes field: choose an attribute field that provides class identifiers for those records, for which the target class is known, and no-data (or empty string) for all other records.
- Training samples: a table with sample records providing the class identifier in the first field followed by sample data corresponding to the selected feature attributes.
- Load statistics from file: loads feature statistics from a file that has been previously stored after training with one of the other two options.
Parameters
| Name | Type | Identifier | Description | Constraints | |
|---|---|---|---|---|---|
| Input | Table | table, input | TABLE | - | - |
| Training Samples | table, input | TRAIN_SAMPLES | Provide a class identifier in the first field followed by sample data corresponding to the selected feature attributes. | - | |
| Output | Classification | table, output, optional | RESULT_TABLE | - | - |
| Classification | shapes, output, optional | RESULT_SHAPES | - | - | |
| Options | Features | table fields | FEATURES | - | - |
| Normalise | boolean | NORMALISE | - | Default: 0 | |
| Training | choice | TRAIN_WITH | - | Available Choices: [0] known classes field [1] training samples [2] load statistics from file Default: 0 | |
| Known Classes Field | table field | TRAIN_FIELD | - | - | |
| Load Statistics from File... | file path | FILE_LOAD | - | - | |
| Save Statistics to File... | file path | FILE_SAVE | - | - | |
| Method | choice | METHOD | - | Available Choices: [0] Binary Encoding [1] Parallelepiped [2] Minimum Distance [3] Mahalanobis Distance [4] Maximum Likelihood [5] Spectral Angle Mapping [6] Winner Takes All Default: 2 | |
| Distance Threshold | floating point number | THRESHOLD_DIST | Let pixel stay unclassified, if minimum euclidian or mahalanobis distance is greater than threshold. | Minimum: 0.000000 Default: 0.000000 | |
| Spectral Angle Threshold (Degree) | floating point number | THRESHOLD_ANGLE | Let pixel stay unclassified, if spectral angle distance is greater than threshold. | Minimum: 0.000000 Maximum: 90.000000 Default: 0.000000 | |
| Probability Threshold | floating point number | THRESHOLD_PROB | Let pixel stay unclassified, if maximum likelihood probability value is less than threshold. | Minimum: 0.000000 Maximum: 100.000000 Default: 0.000000 | |
| Probability Reference | choice | RELATIVE_PROB | - | Available Choices: [0] absolute [1] relative Default: 1 | |
| Binary Encoding | boolean | WTA_0 | - | Default: 0 | |
| Parallelepiped | boolean | WTA_1 | - | Default: 0 | |
| Minimum Distance | boolean | WTA_2 | - | Default: 0 | |
| Mahalanobis Distance | boolean | WTA_3 | - | Default: 0 | |
| Maximum Likelihood | boolean | WTA_4 | - | Default: 0 | |
| Spectral Angle Mapping | boolean | WTA_5 | - | Default: 0 |
Command Line
Usage: saga_cmd table_tools 26 [-TABLE] [-FEATURES ] [-NORMALISE ] [-RESULT_TABLE ] [-RESULT_SHAPES ] [-TRAIN_WITH ] [-TRAIN_FIELD ] [-TRAIN_SAMPLES ] [-FILE_LOAD ] [-FILE_SAVE ] [-METHOD ] [-THRESHOLD_DIST ] [-THRESHOLD_ANGLE ] [-THRESHOLD_PROB ] [-RELATIVE_PROB ] [-WTA_0 ] [-WTA_1 ] [-WTA_2 ] [-WTA_3 ] [-WTA_4 ] [-WTA_5 ] -TABLE: Table table, input -FEATURES: Features table fields -NORMALISE: Normalise boolean Default: 0 -RESULT_TABLE: Classification table, output, optional -RESULT_SHAPES: Classification shapes, output, optional -TRAIN_WITH: Training choice Available Choices: [0] known classes field [1] training samples [2] load statistics from file Default: 0 -TRAIN_FIELD: Known Classes Field table field -TRAIN_SAMPLES: Training Samples table, input -FILE_LOAD: Load Statistics from File... file path -FILE_SAVE: Save Statistics to File... file path -METHOD: Method choice Available Choices: [0] Binary Encoding [1] Parallelepiped [2] Minimum Distance [3] Mahalanobis Distance [4] Maximum Likelihood [5] Spectral Angle Mapping [6] Winner Takes All Default: 2 -THRESHOLD_DIST: Distance Threshold floating point number Minimum: 0.000000 Default: 0.000000 -THRESHOLD_ANGLE: Spectral Angle Threshold (Degree) floating point number Minimum: 0.000000 Maximum: 90.000000 Default: 0.000000 -THRESHOLD_PROB: Probability Threshold floating point number Minimum: 0.000000 Maximum: 100.000000 Default: 0.000000 -RELATIVE_PROB: Probability Reference choice Available Choices: [0] absolute [1] relative Default: 1 -WTA_0: Binary Encoding boolean Default: 0 -WTA_1: Parallelepiped boolean Default: 0 -WTA_2: Minimum Distance boolean Default: 0 -WTA_3: Mahalanobis Distance boolean Default: 0 -WTA_4: Maximum Likelihood boolean Default: 0 -WTA_5: Spectral Angle Mapping boolean Default: 0