KernelMachine.h

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/*
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 1999-2009 Soeren Sonnenburg
 * Written (W) 2011-2012 Heiko Strathmann
 * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
 */

#ifndef _KERNEL_MACHINE_H__
#define _KERNEL_MACHINE_H__

#include <shogun/lib/config.h>

#include <shogun/lib/common.h>
#include <shogun/machine/Machine.h>
#include <shogun/lib/SGVector.h>


namespace shogun
{
class CLabels;
class CBinaryLabels;
class CRegressionLabels;
class CKernel;
class CCustomKernel;
class CFeatures;

class CKernelMachine : public CMachine
{
    public:
        CKernelMachine();

        CKernelMachine(CKernel* k, const SGVector<float64_t> alphas, const SGVector<int32_t> svs, float64_t b);

        CKernelMachine(CKernelMachine* machine);

        virtual ~CKernelMachine();

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

        void set_kernel(CKernel* k);

        CKernel* get_kernel();

        void set_batch_computation_enabled(bool enable);

        bool get_batch_computation_enabled();

        void set_linadd_enabled(bool enable);

        bool get_linadd_enabled();

        void set_bias_enabled(bool enable_bias);

        bool get_bias_enabled();

        float64_t get_bias();

        void set_bias(float64_t bias);

        int32_t get_support_vector(int32_t idx);

        float64_t get_alpha(int32_t idx);

        bool set_support_vector(int32_t idx, int32_t val);

        bool set_alpha(int32_t idx, float64_t val);

        int32_t get_num_support_vectors();

        void set_alphas(SGVector<float64_t> alphas);

        void set_support_vectors(SGVector<int32_t> svs);

        SGVector<int32_t> get_support_vectors();

        SGVector<float64_t> get_alphas();

        bool create_new_model(int32_t num);

        bool init_kernel_optimization();

        virtual CRegressionLabels* apply_regression(CFeatures* data=NULL);

        virtual CBinaryLabels* apply_binary(CFeatures* data=NULL);

        virtual float64_t apply_one(int32_t num);

        static void* apply_helper(void* p);

        virtual bool train_locked(SGVector<index_t> indices);

        virtual CBinaryLabels* apply_locked_binary(SGVector<index_t> indices);

        virtual CRegressionLabels* apply_locked_regression(
                SGVector<index_t> indices);

        virtual SGVector<float64_t> apply_locked_get_output(
                SGVector<index_t> indices);

        virtual void data_lock(CLabels* labs, CFeatures* features=NULL);

        virtual void data_unlock();

        virtual bool supports_locking() const;

    protected:

        SGVector<float64_t> apply_get_outputs(CFeatures* data);

        virtual void store_model_features();

    private:
        void init();

    protected:
        CKernel* kernel;

        CCustomKernel* m_custom_kernel;

        CKernel* m_kernel_backup;

        bool use_batch_computation;

        bool use_linadd;

        bool use_bias;

        float64_t m_bias;

        SGVector<float64_t> m_alpha;

        SGVector<int32_t> m_svs;
};
}
#endif /* _KERNEL_MACHINE_H__ */