#[repr(C)]pub enum SVM_Types {
C_SVC = 100,
NU_SVC = 101,
ONE_CLASS = 102,
EPS_SVR = 103,
NU_SVR = 104,
}
Expand description
%SVM type
Variants§
C_SVC = 100
C-Support Vector Classification. n-class classification (n 2), allows
imperfect separation of classes with penalty multiplier C for outliers.
NU_SVC = 101
-Support Vector Classification. n-class classification with possible
imperfect separation. Parameter
(in the range 0..1, the larger the value, the smoother
the decision boundary) is used instead of C.
ONE_CLASS = 102
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.
EPS_SVR = 103
-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.
NU_SVR = 104
-Support Vector Regression.
is used instead of p.
See LibSVM for details.
Trait Implementations§
impl Copy for SVM_Types
impl Eq for SVM_Types
impl StructuralPartialEq for SVM_Types
Auto Trait Implementations§
impl Freeze for SVM_Types
impl RefUnwindSafe for SVM_Types
impl Send for SVM_Types
impl Sync for SVM_Types
impl Unpin for SVM_Types
impl UnwindSafe for SVM_Types
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
source§impl<T> CloneToUninit for Twhere
T: Clone,
impl<T> CloneToUninit for Twhere
T: Clone,
source§unsafe fn clone_to_uninit(&self, dst: *mut T)
unsafe fn clone_to_uninit(&self, dst: *mut T)
clone_to_uninit
)