Trait opencv::ml::Boost

pub trait Boost: AlgorithmTrait + DTrees + StatModel {
    fn as_raw_Boost(&self) -> *mut c_void;

    fn get_boost_type(&self) -> Result<i32> { ... }
    fn set_boost_type(&mut self, val: i32) -> Result<()> { ... }
    fn get_weak_count(&self) -> Result<i32> { ... }
    fn set_weak_count(&mut self, val: i32) -> Result<()> { ... }
    fn get_weight_trim_rate(&self) -> Result<f64> { ... }
    fn set_weight_trim_rate(&mut self, val: f64) -> Result<()> { ... }
}

Boosted tree classifier derived from DTrees

See also

@ref ml_intro_boost

Required methods

fn as_raw_Boost(&self) -> *mut c_void

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Provided methods

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

Type of the boosting algorithm. See Boost::Types. Default value is Boost::REAL.

See also

setBoostType

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

Type of the boosting algorithm. See Boost::Types. Default value is Boost::REAL.

See also

setBoostType getBoostType

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

The number of weak classifiers. Default value is 100.

See also

setWeakCount

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

The number of weak classifiers. Default value is 100.

See also

setWeakCount getWeakCount

fn get_weight_trim_rate(&self) -> Result<f64>

A threshold between 0 and 1 used to save computational time. Samples with summary weight do not participate in the next iteration of training. Set this parameter to 0 to turn off this functionality. Default value is 0.95.

See also

setWeightTrimRate

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

A threshold between 0 and 1 used to save computational time. Samples with summary weight do not participate in the next iteration of training. Set this parameter to 0 to turn off this functionality. Default value is 0.95.

See also

setWeightTrimRate getWeightTrimRate

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Methods

impl<'_> dyn Boost + '_

pub fn create() -> Result<PtrOfBoost>

Creates the empty model. Use StatModel::train to train the model, Algorithm::load<Boost>(filename) to load the pre-trained model.

pub fn load(filepath: &str, node_name: &str) -> Result<PtrOfBoost>

Loads and creates a serialized Boost from a file

Use Boost::save to serialize and store an RTree to disk. Load the Boost from this file again, by calling this function with the path to the file. Optionally specify the node for the file containing the classifier

Parameters

• filepath: path to serialized Boost
• nodeName: name of node containing the classifier

C++ default parameters

• node_name: String()

Implementors

impl Boost for PtrOfBoost

fn as_raw_Boost(&self) -> *mut c_void

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