SMO
Namespace: Semagle.MachineLearning.SVM
Implementation of Sequential Minimal Optimization (SMO) algorithm
Nested types and modules
| Type | Description |
| C_SMO |
General parameters for C_SMO problem |
| C_SVC |
Optimization parameters for C_SVC problem |
| C_SVR |
Optimization parameters for C_SVR problem |
| OneClass |
Optimization parameters for One-Class problem |
| OptimizationOptions |
Optimization options of SMO algorithm |
| Q |
Interface of Q matrix |
| WSSStrategy |
Working set selection strategy |
Functions and values
| Function or value | Description |
C_SMO X Y Q parameters options
Signature: X:'X [] -> Y:float32 [] -> Q:Q -> parameters:C_SMO -> options:OptimizationOptions -> 'X [] * float32 [] * float [] * float
Type parameters: 'X |
Sequential Minimal Optimization (SMO) problem solver |
C_SVC X Y K parameters options
Signature: X:'X [] -> Y:float32 [] -> K:Kernel<'X> -> parameters:C_SVC -> options:OptimizationOptions -> SVM<'X,'?7884>
Type parameters: 'X, '?7884 |
Two class C Support Vector Classification (SVC) problem solver |
C_SVC_M X Y K parameters options
Signature: X:'X [] -> Y:'Y [] -> K:Kernel<'X> -> parameters:C_SVC -> options:OptimizationOptions -> SVM<'X,'Y>
Type parameters: 'X, 'Y |
Multi-class C Support Vector Classification (SVC) problem solver |
C_SVR X Y K parameters options
Signature: X:'X [] -> Y:float32 [] -> K:Kernel<'X> -> parameters:C_SVR -> options:OptimizationOptions -> SVM<'X,'?7919>
Type parameters: 'X, '?7919 |
C Support Vector Regression (SVR) problem solver |
defaultOptimizationOptions
Signature: OptimizationOptions
|
Default optimization options |
OneClass X K parameters options
Signature: X:'X [] -> K:Kernel<'X> -> parameters:OneClass -> options:OptimizationOptions -> SVM<'X,'?7900>
Type parameters: 'X, '?7900 |
One-Class problem solver |
