Support Vector Machine (SVM) based classification for grids.
| Name | Type | Identifier | Description | Constraints |
Input | Grids | Grid list, input | GRIDS | - | - |
Training Areas | Shapes, input | ROI | - | - |
Output | Classification | Grid, output | CLASSES | - | - |
Look-up Table (*) | Table, output, optional | CLASSES_LUT | A reference list of the grid values that have been assigned to the training classes. | - |
Options | Grid System | Grid system | PARAMETERS_GRID_SYSTEM | - | - |
Scaling | Choice | SCALING | - | Available Choices: [0] none [1] normalize (0-1) [2] standardize Default: 2 |
Verbose Messages | Boolean | MESSAGE | - | Default: 0 |
Model Source | Choice | MODEL_SRC | - | Available Choices: [0] create from training areas [1] restore from file Default: 0 |
Restore Model from File | File path | MODEL_LOAD | - | - |
Class Identifier | Table field | ROI_ID | - | - |
Store Model to File | File path | MODEL_SAVE | - | - |
SVM Type | Choice | SVM_TYPE | - | Available Choices: [0] C-SVC [1] nu-SVC [2] one-class SVM [3] epsilon-SVR [4] nu-SVR Default: 0 |
Kernel Type | Choice | KERNEL_TYPE | linear: u'*v
polynomial: (gamma*u'*v + coef0)^degree
radial basis function: exp(-gamma*|u-v|^2)
sigmoid: tanh(gamma*u'*v + coef0) | Available Choices: [0] linear [1] polynomial [2] radial basis function [3] sigmoid Default: 2 |
Degree | Integer | DEGREE | degree in kernel function | Default: 3 |
Gamma | Floating point | GAMMA | gamma in kernel function | Default: 0.000000 |
coef0 | Floating point | COEF0 | coef0 in kernel function | Default: 0.000000 |
C | Floating point | COST | parameter C (cost) of C-SVC, epsilon-SVR, and nu-SVR | Default: 1.000000 |
nu-SVR | Floating point | NU | parameter nu of nu-SVC, one-class SVM, and nu-SVR | Default: 0.500000 |
SVR Epsilon | Floating point | EPS_SVR | epsilon in loss function of epsilon-SVR | Default: 0.100000 |
Cache Size | Floating point | CACHE_SIZE | cache memory size in MB | Default: 100.000000 |
Epsilon | Floating point | EPS | tolerance of termination criterion | Default: 0.001000 |
Shrinking | Boolean | SHRINKING | whether to use the shrinking heuristics | Default: 0 |
Probability Estimates | Boolean | PROBABILITY | whether to train a SVC or SVR model for probability estimates | Default: 0 |
Cross Validation | Integer | CROSSVAL | n-fold cross validation: n must > 1 | Minimum: 1 Default: 1 |
(*) optional |