L1Penalty.cpp

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/*
 * Copyright (c) The Shogun Machine Learning Toolbox
 * Written (w) 2015 Wu Lin
 * All rights reserved.
 *
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 * modification, are permitted provided that the following conditions are met:
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 *    list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
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#include <shogun/optimization/L1Penalty.h>
#include <shogun/mathematics/Math.h>
using namespace shogun;

float64_t L1Penalty::get_penalty(float64_t variable)
{
    return CMath::abs(variable);
}

void L1Penalty::set_rounding_epsilon(float64_t epsilon)
{
    REQUIRE(epsilon>=0,"Rounding epsilon (%f) should be non-negative\n", epsilon);
    m_rounding_epsilon=epsilon;
}

void L1Penalty::update_variable_for_proximity(SGVector<float64_t> variable,
    float64_t proximal_weight)
{
    for(index_t idx=0; idx<variable.vlen; idx++)
        variable[idx]=get_sparse_variable(variable[idx], proximal_weight);
}

float64_t L1Penalty::get_sparse_variable(float64_t variable, float64_t penalty_weight)
{
    if (variable>0.0)
    {
        variable-=penalty_weight;
        if (variable<0.0)
            variable=0.0;
    }
    else
    {
        variable+=penalty_weight;
        if (variable>0.0)
            variable=0.0;
    }
    if (CMath::abs(variable)<m_rounding_epsilon)
        variable=0.0;
    return variable;
}

void L1Penalty::init()
{
    m_rounding_epsilon=1e-8;
    SG_ADD(&m_rounding_epsilon, "L1Penalty__m_rounding_epsilon",
        "rounding_epsilon in L1Penalty", MS_NOT_AVAILABLE);
}