Tool SVM Classification

Support Vector Machine (SVM) based classification for grids.
Reference:
Chang, C.-C. / Lin, C.-J. (2011): A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, vol.2/3, p.1-27. LIBSVM Homepage.

Author: O.Conrad (c) 2012
Menu: Imagery|Classification|Machine Learning

Parameters

	Name	Type	Identifier	Description	Constraints
Input	Grids	Grid list (input)	`GRIDS`	-	-
Input	Training Areas	Shapes (input)	`ROI`	-	-
Output	Classification	Grid (output)	`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: (gammau'v + coef0)^degree radial basis function: exp(-gamma\|u-v\|^2) sigmoid: tanh(gammau'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

Command-line

Usage: saga_cmd imagery_svm 0 [-GRIDS <str>] [-CLASSES <str>] [-SCALING <str>] [-MESSAGE <str>] [-MODEL_SRC <str>] [-MODEL_LOAD <str>] [-ROI <str>] [-ROI_ID <str>] [-MODEL_SAVE <str>] [-SVM_TYPE <str>] [-KERNEL_TYPE <str>] [-DEGREE <num>] [-GAMMA <double>] [-COEF0 <double>] [-COST <double>] [-NU <double>] [-EPS_SVR <double>] [-CACHE_SIZE <double>] [-EPS <double>] [-SHRINKING <str>] [-PROBABILITY <str>] [-CROSSVAL <num>]
  -GRIDS:<str>        	Grids
	Grid list (input)
  -CLASSES:<str>      	Classification
	Grid (output)
  -SCALING:<str>      	Scaling
	Choice
	Available Choices:
	[0] none
	[1] normalize (0-1)
	[2] standardize
	Default: 2
  -MESSAGE:<str>      	Verbose Messages
	Boolean
	Default: 0
  -MODEL_SRC:<str>    	Model Source
	Choice
	Available Choices:
	[0] create from training areas
	[1] restore from file
	Default: 0
  -MODEL_LOAD:<str>   	Restore Model from File
	File path
  -ROI:<str>          	Training Areas
	Shapes (input)
  -ROI_ID:<str>       	Class Identifier
	Table field
  -MODEL_SAVE:<str>   	Store Model to File
	File path
  -SVM_TYPE:<str>     	SVM Type
	Choice
	Available Choices:
	[0] C-SVC
	[1] nu-SVC
	[2] one-class SVM
	[3] epsilon-SVR
	[4] nu-SVR
	Default: 0
  -KERNEL_TYPE:<str>  	Kernel Type
	Choice
	Available Choices:
	[0] linear
	[1] polynomial
	[2] radial basis function
	[3] sigmoid
	Default: 2
  -DEGREE:<num>       	Degree
	Integer
	Default: 3
  -GAMMA:<double>     	Gamma
	Floating point
	Default: 0.000000
  -COEF0:<double>     	coef0
	Floating point
	Default: 0.000000
  -COST:<double>      	C
	Floating point
	Default: 1.000000
  -NU:<double>        	nu-SVR
	Floating point
	Default: 0.500000
  -EPS_SVR:<double>   	SVR Epsilon
	Floating point
	Default: 0.100000
  -CACHE_SIZE:<double>	Cache Size
	Floating point
	Default: 100.000000
  -EPS:<double>       	Epsilon
	Floating point
	Default: 0.001000
  -SHRINKING:<str>    	Shrinking
	Boolean
	Default: 0
  -PROBABILITY:<str>  	Probability Estimates
	Boolean
	Default: 0
  -CROSSVAL:<num>     	Cross Validation
	Integer
	Minimum: 1
	Default: 1