[][src]Trait opencv::ml::Boost

pub trait Boost: DTrees {
    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

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Provided methods

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

@see setBoostType

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

@copybrief getBoostType @see getBoostType

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

@see setWeakCount

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

@copybrief getWeakCount @see getWeakCount

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

@see setWeightTrimRate

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

@copybrief getWeightTrimRate @see getWeightTrimRate

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Methods

impl<'_> dyn Boost + '_[src]

pub fn create() -> Result<PtrOfBoost>[src]

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>[src]

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[src]

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