Trait opencv::prelude::SVMSGDConst

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pub trait SVMSGDConst: StatModelConst {
    // Required method
    fn as_raw_SVMSGD(&self) -> *const c_void;

    // Provided methods
    fn get_svmsgd_type(&self) -> Result<i32> { ... }
    fn get_margin_type(&self) -> Result<i32> { ... }
    fn get_margin_regularization(&self) -> Result<f32> { ... }
    fn get_initial_step_size(&self) -> Result<f32> { ... }
    fn get_step_decreasing_power(&self) -> Result<f32> { ... }
    fn get_term_criteria(&self) -> Result<TermCriteria> { ... }
}
Expand description

Constant methods for crate::ml::SVMSGD

Required Methods§

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fn as_raw_SVMSGD(&self) -> *const c_void

Provided Methods§

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fn get_svmsgd_type(&self) -> Result<i32>

%Algorithm type, one of SVMSGD::SvmsgdType.

See also

setSvmsgdType

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fn get_margin_type(&self) -> Result<i32>

%Margin type, one of SVMSGD::MarginType.

See also

setMarginType

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fn get_margin_regularization(&self) -> Result<f32>

Parameter marginRegularization of a %SVMSGD optimization problem.

See also

setMarginRegularization

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fn get_initial_step_size(&self) -> Result<f32>

Parameter initialStepSize of a %SVMSGD optimization problem.

See also

setInitialStepSize

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fn get_step_decreasing_power(&self) -> Result<f32>

Parameter stepDecreasingPower of a %SVMSGD optimization problem.

See also

setStepDecreasingPower

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fn get_term_criteria(&self) -> Result<TermCriteria>

Termination criteria of the training algorithm. You can specify the maximum number of iterations (maxCount) and/or how much the error could change between the iterations to make the algorithm continue (epsilon).

See also

setTermCriteria

Implementors§