Trait opencv::ml::Boost

pub trait Boost: BoostConst + DTrees {
    // Required method
    fn as_raw_mut_Boost(&mut self) -> *mut c_void;

    // Provided methods
    fn set_boost_type(&mut self, val: i32) -> Result<()> { ... }
    fn set_weak_count(&mut self, val: i32) -> Result<()> { ... }
    fn set_weight_trim_rate(&mut self, val: f64) -> Result<()> { ... }
}

Boosted tree classifier derived from DTrees

See also

[ml_intro_boost]

Required Methods

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

Provided Methods

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

The number of weak classifiers. Default value is 100.

See also

setWeakCount getWeakCount

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

Implementations

impl dyn Boost + '_

pub fn create() -> Result<Ptr<dyn Boost>>

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<Ptr<dyn Boost>>

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 Ptr<dyn Boost>