libshogun-dev 1.1.0-4ubuntu2 / usr / include / shogun / kernel / MultitaskKernelMaskNormalizer.h

/*
 * 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 2 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 2010 Christian Widmer
 * Copyright (C) 2010 Max-Planck-Society
 */

#ifndef _MULTITASKKERNELMASKNORMALIZER_H___
#define _MULTITASKKERNELMASKNORMALIZER_H___

#include <shogun/kernel/KernelNormalizer.h>
#include <shogun/kernel/Kernel.h>
#include <set>
#include <string>

namespace shogun
{


/** @brief The MultitaskKernel allows Multitask Learning via a modified kernel function.
 *
 * The user defines a set of active tasks. Subsequently, only similarities between active
 * tasks are taken into account. Kernel entries between tasks of which at least one is
 * not an active tasks are set to zero.
 *
 * \f[
 * K_S(x,y)=\left\{\begin{array}{cl} K_B(x,y), & \mbox{if } t(x) \in S \wedge t(y) \in S\\ 0, & \mbox{else} \end{array}\right.
 * \f]
 */
class CMultitaskKernelMaskNormalizer: public CKernelNormalizer
{

public:

	/** default constructor
	 */
	CMultitaskKernelMaskNormalizer() : CKernelNormalizer(),
		scale(1.0), normalization_constant(1.0)
	{
	}

	/** default constructor
	 *
	 * @param task_lhs task vector with containing task_id for each example for left hand side
	 * @param task_rhs task vector with containing task_id for each example for right hand side
	 * @param active_tasks_vec
	 */
	CMultitaskKernelMaskNormalizer(std::vector<int32_t> task_lhs,
								   std::vector<int32_t> task_rhs,
								   std::vector<int32_t> active_tasks_vec)
		: CKernelNormalizer(), scale(1.0), normalization_constant(1.0)
	{


		set_task_vector_lhs(task_lhs);
		set_task_vector_rhs(task_rhs);

		// set active tasks
		for (int32_t i = 0; i != (int32_t)(active_tasks_vec.size()); ++i)
		{
			active_tasks.insert(active_tasks_vec[i]);
		}

	}


	/** default destructor */
	virtual ~CMultitaskKernelMaskNormalizer()
	{
	}

	/** initialization of the normalizer
	 * @param k kernel */
	virtual bool init(CKernel* k)
	{
		ASSERT(k);
		int32_t num_lhs = k->get_num_vec_lhs();
		int32_t num_rhs = k->get_num_vec_rhs();
		ASSERT(num_lhs>0);
		ASSERT(num_rhs>0);


		//same as first-element normalizer
		CFeatures* old_lhs=k->lhs;
		CFeatures* old_rhs=k->rhs;
		k->lhs=old_lhs;
		k->rhs=old_lhs;

		if (std::string(k->get_name()) == "WeightedDegree") {
			SG_INFO("using first-element normalization\n");
			scale=k->compute(0, 0);
		} else {
			SG_INFO("no inner normalization for non-WDK kernel\n");
			scale=1.0;
		}

		k->lhs=old_lhs;
		k->rhs=old_rhs;


		return true;
	}



	/** normalize the kernel value
	 * @param value kernel value
	 * @param idx_lhs index of left hand side vector
	 * @param idx_rhs index of right hand side vector
	 */
	inline virtual float64_t normalize(float64_t value, int32_t idx_lhs, int32_t idx_rhs)
	{

		//lookup tasks
		int32_t task_idx_lhs = task_vector_lhs[idx_lhs];
		int32_t task_idx_rhs = task_vector_rhs[idx_rhs];

		//lookup similarity
		float64_t task_similarity = get_similarity(task_idx_lhs, task_idx_rhs);

		//take task similarity into account
		float64_t similarity = (value/scale) * task_similarity;


		return similarity;

	}

	/** normalize only the left hand side vector
	 * @param value value of a component of the left hand side feature vector
	 * @param idx_lhs index of left hand side vector
	 */
	inline virtual float64_t normalize_lhs(float64_t value, int32_t idx_lhs)
	{
		SG_ERROR("normalize_lhs not implemented");
		return 0;
	}

	/** normalize only the right hand side vector
	 * @param value value of a component of the right hand side feature vector
	 * @param idx_rhs index of right hand side vector
	 */
	inline virtual float64_t normalize_rhs(float64_t value, int32_t idx_rhs)
	{
		SG_ERROR("normalize_rhs not implemented");
		return 0;
	}

	/** @return vec task vector with containing task_id for each example on left hand side */
	std::vector<int32_t> get_task_vector_lhs() const
	{
		return task_vector_lhs;
	}


	/** @param vec task vector with containing task_id for each example */
	void set_task_vector_lhs(std::vector<int32_t> vec)
	{

		task_vector_lhs.clear();

		for (int32_t i = 0; i != (int32_t)(vec.size()); ++i)
		{
			task_vector_lhs.push_back(vec[i]);
		}

	}

	/** @return vec task vector with containing task_id for each example on right hand side */

	std::vector<int32_t> get_task_vector_rhs() const
	{
		return task_vector_rhs;
	}


	/** @param vec task vector with containing task_id for each example */
	void set_task_vector_rhs(std::vector<int32_t> vec)
	{

		task_vector_rhs.clear();

		for (int32_t i = 0; i != (int32_t)(vec.size()); ++i)
		{
			task_vector_rhs.push_back(vec[i]);
		}

	}

	/** @param vec task vector with containing task_id for each example */
	void set_task_vector(std::vector<int32_t> vec)
	{
		set_task_vector_lhs(vec);
		set_task_vector_rhs(vec);
	}


	/**
	 * @param task_lhs task_id on left hand side
	 * @param task_rhs task_id on right hand side
	 * @return similarity between tasks
	 */
	float64_t get_similarity(int32_t task_lhs, int32_t task_rhs)
	{

		const bool lhs_is_in = active_tasks.find(task_lhs) != active_tasks.end();
		const bool rhs_is_in = active_tasks.find(task_rhs) != active_tasks.end();

		float64_t similarity = 0.0;

		if (lhs_is_in && rhs_is_in)
		{
			similarity = 1.0 / normalization_constant;
		}

		return similarity;

	}

	/**
	 * @return list of active task ids
	 */
	std::vector<int32_t> get_active_tasks()
	{

		std::vector<int32_t> active_tasks_vec;

		// set active tasks
		for (std::set<int32_t>::const_iterator it=active_tasks.begin(); it!=active_tasks.end(); it++)
		{
			active_tasks_vec.push_back(*it);
		}

		return active_tasks_vec;
	}

	/**
	 * @return normalization constant
	 */
	float64_t get_normalization_constant () const
	{
		return normalization_constant;
	}

	/**
	 * @param constant normalization constant
	 */
	float64_t set_normalization_constant(float64_t constant)
	{
		normalization_constant = constant;

		SG_NOTIMPLEMENTED;
		return 0.0;
	}

	/** @return object name */
	inline virtual const char* get_name() const
	{
		return "MultitaskKernelMaskNormalizer";
	}

	/** casts kernel normalizer to multitask kernel mask normalizer
	 * @param n kernel normalizer to cast
	 */
	CMultitaskKernelMaskNormalizer* KernelNormalizerToMultitaskKernelMaskNormalizer(CKernelNormalizer* n)
	{
		   return dynamic_cast<CMultitaskKernelMaskNormalizer*>(n);
	}

protected:
	/** list of active tasks **/
	std::set<int32_t> active_tasks;

	/** task vector indicating to which task each example on the left hand side belongs **/
	std::vector<int32_t> task_vector_lhs;

	/** task vector indicating to which task each example on the right hand side belongs **/
	std::vector<int32_t> task_vector_rhs;

	/** value of first element **/
	float64_t scale;

	/** outer normalization constant **/
	float64_t normalization_constant;

};
}
#endif