StudentsTVGLikelihood.h

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2014 Wu Lin
 * 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
 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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 * The views and conclusions contained in the software and documentation are those
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 * either expressed or implied, of the Shogun Development Team.
 *
 * Code adapted from
 * http://hannes.nickisch.org/code/approxXX.tar.gz
 * and the reference paper is
 * Nickisch, Hannes, and Carl Edward Rasmussen.
 * "Approximations for Binary Gaussian Process Classification."
 * Journal of Machine Learning Research 9.10 (2008).
 */

#ifndef  _STUDENTSTVGLIKELIHOOD_H_
#define  _STUDENTSTVGLIKELIHOOD_H_

#include <shogun/lib/config.h>

#include <shogun/machine/gp/NumericalVGLikelihood.h>

namespace shogun
{
template<class C> class SGMatrix;

class CStudentsTVGLikelihood : public CNumericalVGLikelihood
{
public:
    CStudentsTVGLikelihood();

    CStudentsTVGLikelihood(float64_t sigma, float64_t df);

    virtual ~CStudentsTVGLikelihood();

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

    virtual bool supports_derivative_wrt_hyperparameter() const { return true; }

protected:
    virtual void init_likelihood();

private:

    void init();

    float64_t m_log_sigma;
    float64_t m_log_df;

};
}
#endif /* _STUDENTSTVGLIKELIHOOD_H_ */