RemoveBudgetMaintenanceStrategy.h

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//===========================================================================
/*!
 *
 *
 * \brief       Remove budget maintenance strategy.
 *
 * \par
 * This is an budget strategy that simply removes one of the
 * budget vectors. Depending on the flavor, this can be e.g.
 * a random one, the smallest one (w.r.t. to 2-norm of the alphas)
 *
 *
 *
 *
 * \author      Aydin Demircioglu
 * \date        2014
 *
 *
 * \par Copyright 1995-2017 Shark Development Team
 *
 * <BR><HR>
 * This file is part of Shark.
 * <https://shark-ml.github.io/Shark/>
 *
 * Shark is free software: you can redistribute it and/or modify
 * it under the terms of the GNU Lesser General Public License as published
 * by the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * Shark is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public License
 * along with Shark.  If not, see <http://www.gnu.org/licenses/>.
 *
 */
//===========================================================================
 
 
#ifndef SHARK_MODELS_REMOVEBUDGETMAINTENANCESTRATEGY_H
#define SHARK_MODELS_REMOVEBUDGETMAINTENANCESTRATEGY_H
 
#include <shark/Models/Kernels/AbstractKernelFunction.h>
#include <shark/Data/Dataset.h>
#include <shark/Data/DataView.h>
 
#include <shark/Algorithms/Trainers/Budgeted/AbstractBudgetMaintenanceStrategy.h>
 
 
namespace shark
{
 
///
/// \brief Budget maintenance strategy that removes a vector
///
/// This is an budget strategy that simply removes one of the
/// budget vectors. Depending on the flavor, this can be e.g.
/// a random one, the smallest one (w.r.t. to 2-norm of the alphas)
///
template<class InputType>
class RemoveBudgetMaintenanceStrategy: public AbstractBudgetMaintenanceStrategy<InputType>
{
    typedef KernelExpansion<InputType> ModelType;
    typedef LabeledData<InputType, unsigned int> DataType;
    typedef typename DataType::element_type ElementType;
 
public:
 
    /// the flavors of the remove strategy
    enum RemoveStrategyFlavor {RANDOM = 0, SMALLEST = 1};
 
 
    /// constructor.
    /// @param[in] flavor   enum that decides on the method a vector is removed.
    RemoveBudgetMaintenanceStrategy(RemoveStrategyFlavor flavor = SMALLEST)
        : m_flavor(flavor)
    {
        SHARK_RUNTIME_CHECK(flavor < 2, "Invalid flavor");
    }
 
 
    /// add a vector to the model.
    /// this will add the given vector to the model and remove another one depending on the flavor.
    ///
    /// @param[in,out]  model   the model the strategy will work with
    /// @param[in]  alpha   alphas for the new budget vector
    /// @param[in]  supportVector the vector to add to the model by applying the maintenance strategy
    ///
    virtual void addToModel(ModelType& model, InputType const& alpha, ElementType const& supportVector)
    {
 
        // first we check: if the budget is not full, we do not need to do remove anything
        std::size_t index = 0;
        double minAlpha = 0;
        this->findSmallestVector(model, index, minAlpha);
 
        if(minAlpha == 0.0f)
        {
            // replace vector and alpha
            model.basis().element(index) = supportVector.input;
            row(model.alpha(), index) = alpha;
            return;
        }
 
        // else depending on the flavor we do something
        switch(m_flavor)
        {
        case RANDOM:
        {
            // though we have found the smallest one,  we want to remove
            // a random element.
            index = random::discrete(0, model.basis().numberOfElements() - 1);
            break;
        }
        case SMALLEST:
        {
            // we already have found the smallest alpha, so nothing to do
            break;
        }
        }
 
        // replace vector and alpha
        model.basis().element(index) = supportVector.input;
        row(model.alpha(), index) = alpha;
 
                // we need to clear out the last vector, as it is just a buffer
                row (model.alpha(), model.basis().numberOfElements() -1).clear();
    }
 
 
    /// class name
    std::string name() const
    { return "RemoveBudgetMaintenanceStrategy"; }
 
protected:
    /// flavor for removing a vector
    size_t m_flavor;
};
 
}
#endif