OpenANN::Bagging Class Reference

Bootstrap Aggregating. More...

#include <Bagging.h>

Inheritance diagram for OpenANN::Bagging:

Public Member Functions
	Bagging (double bagSize)
virtual EnsembleLearner &	addLearner (Learner &learner)
virtual EnsembleLearner &	setOptimizer (Optimizer &optimizer)
virtual EnsembleLearner &	train (DataSet &dataSet)
virtual Eigen::MatrixXd	operator() (Eigen::MatrixXd &X)
virtual Eigen::VectorXd	operator() (Eigen::VectorXd &x)
Public Member Functions inherited from OpenANN::EnsembleLearner
virtual	~EnsembleLearner ()

Detailed Description

Bootstrap Aggregating.

Bagging averages instable learners that have been trained on randomly sampled subsets of the training set [1]. This implementation can be used for classification and regression.

[1] L. Breiman: Bagging Predictors, Machine Learning 24, pp. 123-140, 1996.

Constructor & Destructor Documentation

OpenANN::Bagging::Bagging

(

double

bagSize)

Member Function Documentation

virtual EnsembleLearner& OpenANN::Bagging::addLearner ( Learner &  learner)

virtual

Implements OpenANN::EnsembleLearner.

virtual Eigen::MatrixXd OpenANN::Bagging::operator() ( Eigen::MatrixXd &  X)

virtual

Implements OpenANN::EnsembleLearner.

virtual Eigen::VectorXd OpenANN::Bagging::operator() ( Eigen::VectorXd &  x)

virtual

Implements OpenANN::EnsembleLearner.

virtual EnsembleLearner& OpenANN::Bagging::setOptimizer ( Optimizer &  optimizer)

virtual

Implements OpenANN::EnsembleLearner.

virtual EnsembleLearner& OpenANN::Bagging::train ( DataSet &  dataSet)

virtual

Implements OpenANN::EnsembleLearner.

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The documentation for this class was generated from the following file:

• OpenANN/Bagging.h