Inheritance diagram for mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >:

Public Member Functions
	AdaBoost (const MatType &data, const arma::Row< size_t > &labels, const WeakLearnerType &other, const size_t iterations=100, const double tolerance=1e-6)
	Constructor. More...

	AdaBoost (const double tolerance=1e-6)
	Create the AdaBoost object without training. More...

double	Alpha (const size_t i) const
	Get the weights for the given weak learner. More...

double &	Alpha (const size_t i)
	Modify the weight for the given weak learner (be careful!). More...

size_t	Classes () const
	Get the number of classes this model is trained on. More...

void	Classify (const MatType &test, arma::Row< size_t > &predictedLabels)
	Classify the given test points. More...

template<typename Archive >
void	Serialize (Archive &ar, const unsigned int)
	Serialize the AdaBoost model. More...

double	Tolerance () const
	Get the tolerance for stopping the optimization during training. More...

double &	Tolerance ()
	Modify the tolerance for stopping the optimization during training. More...

void	Train (const MatType &data, const arma::Row< size_t > &labels, const WeakLearnerType &learner, const size_t iterations=100, const double tolerance=1e-6)
	Train AdaBoost on the given dataset. More...

const WeakLearnerType &	WeakLearner (const size_t i) const
	Get the given weak learner. More...

WeakLearnerType &	WeakLearner (const size_t i)
	Modify the given weak learner (be careful!). More...

size_t	WeakLearners () const
	Get the number of weak learners in the model. More...

double	ZtProduct ()

Private Attributes
std::vector< double >	alpha
	The weights corresponding to each weak learner. More...

size_t	classes
	The number of classes in the model. More...

double	tolerance

std::vector< WeakLearnerType >	wl
	The vector of weak learners. More...

double	ztProduct
	To check for the bound for the Hamming loss. More...

Detailed Description

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>
class mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >

The AdaBoost class.

AdaBoost is a boosting algorithm, meaning that it combines an ensemble of weak learners to produce a strong learner. For more information on AdaBoost, see the following paper:

@article{schapire1999improved,
  author = {Schapire, Robert E. and Singer, Yoram},
  title = {Improved Boosting Algorithms Using Confidence-rated Predictions},
  journal = {Machine Learning},
  volume = {37},
  number = {3},
  month = dec,
  year = {1999},
  issn = {0885-6125},
  pages = {297--336},
}

This class is general, and can be used with any type of weak learner, so long as the learner implements the following functions:

// A boosting constructor, which learns using the training parameters of the
// given other WeakLearner, but uses the given instance weights for training.
WeakLearner(WeakLearner& other,
            const MatType& data,
            const arma::Row<size_t>& labels,
            const arma::rowvec& weights);
// Given the test points, classify them and output predictions into
// predictedLabels.
void Classify(const MatType& data, arma::Row<size_t>& predictedLabels);

For more information on and examples of weak learners, see perceptron::Perceptron<> and decision_stump::DecisionStump<>.

Template Parameters

MatType	Data matrix type (i.e. arma::mat or arma::sp_mat).
WeakLearnerType	Type of weak learner to use.

Definition at line 81 of file adaboost.hpp.

Constructor & Destructor Documentation

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::AdaBoost	(	const MatType &	data,
		const arma::Row< size_t > &	labels,
		const WeakLearnerType &	other,
		const size_t	iterations = `100`,
		const double	tolerance = `1e-6`
	)

Constructor.

This runs the AdaBoost.MH algorithm to provide a trained boosting model. This constructor takes an already-initialized weak learner; all other weak learners will learn with the same parameters as the given weak learner.

Parameters

data	Input data.
labels	Corresponding labels.
iterations	Number of boosting rounds.
tol	The tolerance for change in values of rt.
other	Weak learner that has already been initialized.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::AdaBoost ( const double tolerance = 1e-6 )

Create the AdaBoost object without training.

Be sure to call Train() before calling Classify()!

Member Function Documentation

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

double mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::Alpha ( const size_t i ) const

inline

Get the weights for the given weak learner.

Definition at line 123 of file adaboost.hpp.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

double& mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::Alpha ( const size_t i )

inline

Modify the weight for the given weak learner (be careful!).

Definition at line 125 of file adaboost.hpp.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

size_t mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::Classes ( ) const

inline

Get the number of classes this model is trained on.

Definition at line 117 of file adaboost.hpp.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

void mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::Classify	(	const MatType &	test,
		arma::Row< size_t > &	predictedLabels
	)

Classify the given test points.

Parameters

test	Testing data.
predictedLabels	Vector in which to the predicted labels of the test set will be stored.

Referenced by mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::WeakLearner().

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

template<typename Archive >

void mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::Serialize	(	Archive &	ar,
		const unsigned	int
	)

Serialize the AdaBoost model.

Referenced by mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::WeakLearner().

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

double mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::Tolerance ( ) const

inline

Get the tolerance for stopping the optimization during training.

Definition at line 112 of file adaboost.hpp.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

double& mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::Tolerance ( )

inline

Modify the tolerance for stopping the optimization during training.

Definition at line 114 of file adaboost.hpp.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

void mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::Train	(	const MatType &	data,
		const arma::Row< size_t > &	labels,
		const WeakLearnerType &	learner,
		const size_t	iterations = `100`,
		const double	tolerance = `1e-6`
	)

Train AdaBoost on the given dataset.

This method takes an initialized WeakLearnerType; the parameters for this weak learner will be used to train each of the weak learners during AdaBoost training. Note that this will completely overwrite any model that has already been trained with this object.

Parameters

data	Dataset to train on.
labels	Labels for each point in the dataset.
learner	Learner to use for training.

Referenced by mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::WeakLearner().

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

const WeakLearnerType& mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::WeakLearner ( const size_t i ) const

inline

Get the given weak learner.

Definition at line 128 of file adaboost.hpp.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

WeakLearnerType& mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::WeakLearner ( const size_t i )

inline

Modify the given weak learner (be careful!).

Definition at line 130 of file adaboost.hpp.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

size_t mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::WeakLearners ( ) const

inline

Get the number of weak learners in the model.

Definition at line 120 of file adaboost.hpp.

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

double mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::ZtProduct ( )

inline

Definition at line 109 of file adaboost.hpp.

Member Data Documentation

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

std::vector<double> mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::alpha

private

The weights corresponding to each weak learner.

Definition at line 173 of file adaboost.hpp.

Referenced by mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::Alpha(), and mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::WeakLearners().

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

size_t mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::classes

private

The number of classes in the model.

Definition at line 166 of file adaboost.hpp.

Referenced by mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::Classes().

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

double mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::tolerance

private

Definition at line 168 of file adaboost.hpp.

Referenced by mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::Tolerance(), and mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::WeakLearner().

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

std::vector<WeakLearnerType> mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::wl

private

The vector of weak learners.

Definition at line 171 of file adaboost.hpp.

Referenced by mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::WeakLearner().

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>

double mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >::ztProduct

private

To check for the bound for the Hamming loss.

Definition at line 176 of file adaboost.hpp.

Referenced by mlpack::adaboost::AdaBoost< decision_stump::DecisionStump<> >::ZtProduct().

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

src/mlpack/methods/adaboost/adaboost.hpp

Public Member Functions

Private Attributes

Detailed Description

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat> class mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>, typename MatType = arma::mat>
class mlpack::adaboost::AdaBoost< WeakLearnerType, MatType >