Supervised classification for attribute data. To train the classifier choose an attribute that provides class identifiers for those records, for which the target class is known, and no data for all other records.
| Name | Type | Identifier | Description | Constraints |
Input | Shapes | Shapes, input | SHAPES | - | - |
Output | Classification | Shapes, output | CLASSES | - | - |
Options | Features | Table fields | FEATURES | - | - |
Normalise | Boolean | NORMALISE | - | Default: 0 |
Training Classes (*) | Table field | TRAINING | - | - |
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 | 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 | 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 | 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 |
(*) optional |