Trait opencv::ml::LogisticRegressionTrait

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pub trait LogisticRegressionTrait: LogisticRegressionTraitConst + StatModelTrait {
    // Required method
    fn as_raw_mut_LogisticRegression(&mut self) -> *mut c_void;

    // Provided methods
    fn set_learning_rate(&mut self, val: f64) -> Result<()> { ... }
    fn set_iterations(&mut self, val: i32) -> Result<()> { ... }
    fn set_regularization(&mut self, val: i32) -> Result<()> { ... }
    fn set_train_method(&mut self, val: i32) -> Result<()> { ... }
    fn set_mini_batch_size(&mut self, val: i32) -> Result<()> { ... }
    fn set_term_criteria(&mut self, val: TermCriteria) -> Result<()> { ... }
}

Expand description

Mutable methods for crate::ml::LogisticRegression

Required Methods§

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fn as_raw_mut_LogisticRegression(&mut self) -> *mut c_void

Provided Methods§

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fn set_learning_rate(&mut self, val: f64) -> Result<()>

Learning rate.

§See also

setLearningRate getLearningRate

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fn set_iterations(&mut self, val: i32) -> Result<()>

Number of iterations.

§See also

setIterations getIterations

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fn set_regularization(&mut self, val: i32) -> Result<()>

Kind of regularization to be applied. See LogisticRegression::RegKinds.

§See also

setRegularization getRegularization

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fn set_train_method(&mut self, val: i32) -> Result<()>

Kind of training method used. See LogisticRegression::Methods.

§See also

setTrainMethod getTrainMethod

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fn set_mini_batch_size(&mut self, val: i32) -> Result<()>

Specifies the number of training samples taken in each step of Mini-Batch Gradient Descent. Will only be used if using LogisticRegression::MINI_BATCH training algorithm. It has to take values less than the total number of training samples.