Enum opencv::ml::SVM_KernelTypes[][src]

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

%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. image

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. inline formula.

POLY

Polynomial kernel: inline formula.

RBF

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

SIGMOID

Sigmoid kernel: inline formula.

CHI2

Exponential Chi2 kernel, similar to the RBF kernel: inline formula.

INTER

Histogram intersection kernel. A fast kernel. inline formula.

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