Enum opencv::ml::SVM_KernelTypes

#[repr(C)]
pub enum SVM_KernelTypes {
    CUSTOM,
    LINEAR,
    POLY,
    RBF,
    SIGMOID,
    CHI2,
    INTER,
}

%SVM kernel type

A comparison of different kernels on the following 2D test case with four classes. Four SVM::C_SVC SVMs have been trained (one against rest) with auto_train. Evaluation on three different kernels (SVM::CHI2, SVM::INTER, SVM::RBF). The color depicts the class with max score. Bright means max-score > 0, dark means max-score < 0.

Variants

CUSTOM

Returned by SVM::getKernelType in case when custom kernel has been set

LINEAR

Linear kernel. No mapping is done, linear discrimination (or regression) is done in the original feature space. It is the fastest option. .

POLY

Polynomial kernel: .

RBF

Radial basis function (RBF), a good choice in most cases. .

SIGMOID

Sigmoid kernel: .

CHI2

Exponential Chi2 kernel, similar to the RBF kernel: .

INTER

Histogram intersection kernel. A fast kernel. .

Trait Implementations

impl Clone for SVM_KernelTypes

fn clone(&self) -> SVM_KernelTypes

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for SVM_KernelTypes

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq<SVM_KernelTypes> for SVM_KernelTypes

fn eq(&self, other: &SVM_KernelTypes) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Copy for SVM_KernelTypes

impl Eq for SVM_KernelTypes

impl StructuralEq for SVM_KernelTypes

impl StructuralPartialEq for SVM_KernelTypes