ExactInferenceMethod.h

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (W) 2013 Roman Votyakov
 * Written (W) 2012 Jacob Walker
 * 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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 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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 */
#ifndef CEXACTINFERENCEMETHOD_H_
#define CEXACTINFERENCEMETHOD_H_

#include <shogun/lib/config.h>


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

namespace shogun
{

class CExactInferenceMethod: public CInference
{
public:
    CExactInferenceMethod();

    CExactInferenceMethod(CKernel* kernel, CFeatures* features,
            CMeanFunction* mean, CLabels* labels, CLikelihoodModel* model);

    virtual ~CExactInferenceMethod();

    virtual EInferenceType get_inference_type() const { return INF_EXACT; }

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

    static CExactInferenceMethod* obtain_from_generic(CInference* inference);

    virtual float64_t get_negative_log_marginal_likelihood();

    virtual SGVector<float64_t> get_alpha();

    virtual SGMatrix<float64_t> get_cholesky();

    virtual SGVector<float64_t> get_diagonal_vector();

    virtual SGVector<float64_t> get_posterior_mean();

    virtual SGMatrix<float64_t> get_posterior_covariance();

    virtual bool supports_regression() const
    {
        check_members();
        return m_model->supports_regression();
    }

    virtual void update();

    virtual void register_minimizer(Minimizer* minimizer);
protected:
    virtual void check_members() const;

    virtual void update_alpha();

    virtual void update_chol();

    virtual void update_mean();

    virtual void update_cov();

    virtual void update_deriv();

    virtual SGVector<float64_t> get_derivative_wrt_inference_method(
            const TParameter* param);

    virtual SGVector<float64_t> get_derivative_wrt_likelihood_model(
            const TParameter* param);

    virtual SGVector<float64_t> get_derivative_wrt_kernel(
            const TParameter* param);

    virtual SGVector<float64_t> get_derivative_wrt_mean(
            const TParameter* param);

    virtual void compute_gradient();
private:
    SGMatrix<float64_t> m_Sigma;

    SGVector<float64_t> m_mu;

    SGMatrix<float64_t> m_Q;
};
}
#endif /* CEXACTINFERENCEMETHOD_H_ */