| Tool Name | Support Vector Machine Classification |
| Tool ID | 7 |
| Library ID | imagery_opencv |
| Version | 1.0 |
| Author(s) | O.Conrad (c) 2016 |
Change, C.-C. & Lin, C.-J. (2011): Libsvm: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST), 2(3):27. doi:10.1145/1961189.1961199
OpenCV - Open Source Computer Vision
OpenCV - Machine Learning Overview
| Name | Type | Identifier | Description | Constraints |
|---|---|---|---|---|
| Input | ||||
| Features | grid list, input | FEATURES | ||
| Training Samples | table, input | TRAIN_SAMPLES | Provide a class identifier in the first field followed by sample data corresponding to the input feature grids. | |
| Training Areas | shapes, input | TRAIN_AREAS | ||
| 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 | ||||
| Normalize | boolean | NORMALIZE | Default: 0 | |
| Training | choice | MODEL_TRAIN | Available Choices: [0] training areas [1] training samples [2] load from file Default: 0 | |
| Class Identifier | table field | TRAIN_CLASS | ||
| Buffer Size | floating point number | TRAIN_BUFFER | For non-polygon type training areas, creates a buffer with a diameter of specified size. | Minimum: 0.000000 Default: 1.000000 |
| Load Model | file path | MODEL_LOAD | Use a model previously stored to file. | |
| Save Model | file path | MODEL_SAVE | Stores model to file to be used for subsequent classifications instead of training areas. | |
| SVM Type | choice | SVM_TYPE | Available Choices: [0] c-support vector classification [1] nu support vector classification [2] distribution estimation (one class) [3] epsilon support vector regression [4] nu support vector regression Default: 0 | |
| C | floating point number | C | Minimum: 0.000000 Default: 5.000000 | |
| Nu | floating point number | NU | Minimum: 0.000000 Default: 0.500000 | |
| P | floating point number | P | Minimum: 0.000000 Default: 0.500000 | |
| Kernel Type | choice | KERNEL | Available Choices: [0] linear [1] polynomial [2] radial basis function [3] sigmoid [4] exponential chi2 [5] histogram intersection Default: 2 | |
| Coefficient 0 | floating point number | COEF0 | Minimum: 0.000000 Default: 1.000000 | |
| Degree | floating point number | DEGREE | Minimum: 0.000000 Default: 0.500000 | |
| Gamma | floating point number | GAMMA | Minimum: 0.000000 Default: 5.000000 | |