KernelSelection.h

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2012-2013 Heiko Strathmann
 * Written (w) 2014 Soumyajit De
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this
 *    list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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 */

#ifndef KERNEL_SELECTION_H_
#define KERNEL_SELECTION_H_

#include <shogun/lib/config.h>
#include <shogun/base/SGObject.h>

namespace shogun
{

class CKernelTwoSampleTest;
class CKernel;

class CKernelSelection: public CSGObject
{
public:
    CKernelSelection();

    CKernelSelection(CKernelTwoSampleTest* estimator);

    virtual ~CKernelSelection();

    virtual SGVector<float64_t> compute_measures()=0;

    virtual CKernel* select_kernel()=0;

    void set_estimator(CKernelTwoSampleTest* estimator);

    CKernelTwoSampleTest* get_estimator() const;

    virtual const char* get_name() const
    {
        return "KernelSelection";
    }

private:
    void init();

protected:
    CKernelTwoSampleTest* m_estimator;
};

}

#endif /* KERNEL_SELECTION_H_ */