ml_Boost
import { ml_Boost } from '@banou/opencv-wasm'Use after await initOpenCV(). See the initialization and named imports guide.
Native object: release it with using or delete(). Factories can return null; check before calling methods. Inherits ml_DTrees.
Boosted tree classifier *
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Boosted tree classifier derived from DTrees
See: ml_intro_boost
Constructors and members
static create
Creates the empty model. Use StatModel::train to train the model, Algorithm::load<Boost>(filename) to load the pre-trained model.
create(): ml_Boost | null;The ml_Boost | null result.
static load
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
load(filepath: EmbindString, nodeName: EmbindString): ml_Boost | null;2 available overloads
load(filepath: EmbindString): ml_Boost | null;load(filepath: EmbindString, nodeName: EmbindString): ml_Boost | null;filepathpath to serialized Boost
nodeNamename of node containing the classifier
The ml_Boost | null result.
clone
Create another handle to the same native object. This retains the object without copying its pixels or algorithm state; dispose both handles separately.
clone(): this;The this result.
getBoostType
Type of the boosting algorithm. See Boost::Types. Default value is Boost::REAL. See: setBoostType
getBoostType(): number;The number result.
setBoostType
Type of the boosting algorithm. See Boost::Types. Default value is Boost::REAL. See: setBoostType See: getBoostType
setBoostType(val: number): void;valval argument (number).
getWeakCount
The number of weak classifiers. Default value is 100. See: setWeakCount
getWeakCount(): number;The number result.
setWeakCount
The number of weak classifiers. Default value is 100. See: setWeakCount See: getWeakCount
setWeakCount(val: number): void;valval argument (number).
getWeightTrimRate
A threshold between 0 and 1 used to save computational time.
Samples with summary weight \leq 1 - weight_trim_rate 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: setWeightTrimRate
getWeightTrimRate(): number;The number result.
setWeightTrimRate
A threshold between 0 and 1 used to save computational time.
Samples with summary weight \leq 1 - weight_trim_rate 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: setWeightTrimRate See: getWeightTrimRate
setWeightTrimRate(val: number): void;valval argument (number).
These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.