ml_SVM_Types
import { ml_SVM_Types } from '@banou/opencv-wasm'Use after await initOpenCV(). See the initialization and named imports guide.
Native object: release it with using or delete(). Factories can return null; check before calling methods.
ml_SVM_Types: %SVM type
Constructors and members
static C_SVC
C-Support Vector Classification. n-class classification (n \geq 2), allows
imperfect separation of classes with penalty multiplier C for outliers.
C_SVC: ml_SVM_TypesValue<100>,static NU_SVC
\nu-Support Vector Classification. n-class classification with possible
imperfect separation. Parameter \nu (in the range 0..1, the larger the value, the smoother
the decision boundary) is used instead of C.
NU_SVC: ml_SVM_TypesValue<101>,static ONE_CLASS
Distribution Estimation (One-class %SVM). All the training data are from the same class, %SVM builds a boundary that separates the class from the rest of the feature space.
ONE_CLASS: ml_SVM_TypesValue<102>,static EPS_SVR
\epsilon-Support Vector Regression. The distance between feature vectors
from the training set and the fitting hyper-plane must be less than p. For outliers the
penalty multiplier C is used.
EPS_SVR: ml_SVM_TypesValue<103>,static NU_SVR
\nu-Support Vector Regression. \nu is used instead of p.
See [LibSVM] for details.
NU_SVR: ml_SVM_TypesValue<104>These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.