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Reformatting Labels to fix indentation before changing.
Cleaning imports in class CLabels. Cleaning imports in class MultilabelLabels. Adding missing preamble to BinaryLabels.cpp. Cleaning imports in class CBinaryLabels. Formatting BinaryLabels.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,117 +1,140 @@ | ||
| #include <shogun/labels/DenseLabels.h> | ||
| #include <shogun/labels/BinaryLabels.h> | ||
| #include <shogun/mathematics/Statistics.h> | ||
|
|
||
| using namespace shogun; | ||
|
|
||
| CBinaryLabels::CBinaryLabels() : CDenseLabels() | ||
| { | ||
| } | ||
|
|
||
| CBinaryLabels::CBinaryLabels(int32_t num_labels) : CDenseLabels(num_labels) | ||
| { | ||
| } | ||
|
|
||
| #if !defined(SWIGJAVA) && !defined(SWIGCSHARP) | ||
| CBinaryLabels::CBinaryLabels(SGVector<int32_t> src) : CDenseLabels() | ||
| { | ||
| SGVector<float64_t> values(src.vlen); | ||
| for (int32_t i=0; i<values.vlen; i++) | ||
| values[i] = src[i]; | ||
| set_int_labels(src); | ||
| set_values(values); | ||
| } | ||
|
|
||
| CBinaryLabels::CBinaryLabels(SGVector<int64_t> src) : CDenseLabels() | ||
| { | ||
| SGVector<float64_t> values(src.vlen); | ||
| for (int32_t i=0; i<values.vlen; i++) | ||
| values[i] = src[i]; | ||
| set_int_labels(src); | ||
| set_values(values); | ||
| } | ||
| #endif | ||
|
|
||
| CBinaryLabels::CBinaryLabels(SGVector<float64_t> src, float64_t threshold) : CDenseLabels() | ||
| { | ||
| SGVector<float64_t> labels(src.vlen); | ||
| for (int32_t i=0; i<labels.vlen; i++) | ||
| labels[i] = src[i]+threshold>=0 ? +1.0 : -1.0; | ||
| set_labels(labels); | ||
| set_values(src); | ||
| } | ||
|
|
||
| CBinaryLabels::CBinaryLabels(CFile* loader) : CDenseLabels(loader) | ||
| { | ||
| } | ||
|
|
||
| void CBinaryLabels::ensure_valid(const char* context) | ||
| { | ||
| CDenseLabels::ensure_valid(context); | ||
| bool found_plus_one=false; | ||
| bool found_minus_one=false; | ||
|
|
||
| int32_t subset_size=get_num_labels(); | ||
| for (int32_t i=0; i<subset_size; i++) | ||
| { | ||
| int32_t real_i=m_subset_stack->subset_idx_conversion(i); | ||
| if (m_labels[real_i]==+1.0) | ||
| found_plus_one=true; | ||
| else if (m_labels[real_i]==-1.0) | ||
| found_minus_one=true; | ||
| else | ||
| { | ||
| SG_ERROR( | ||
| "%s%s%s::ensure_valid(): Not a two class labeling label[%d]=%f (only +1/-1 " | ||
| "allowed)\n", context ? context : "", | ||
| context ? ": " : "", get_name(), i, m_labels[real_i]); | ||
| } | ||
| } | ||
|
|
||
| if (!found_plus_one) | ||
| { | ||
| SG_WARNING( | ||
| "%s%s%s::ensure_valid(): Not a two class labeling - no positively labeled examples found\n", | ||
| context ? context : "", context ? ": " : "", get_name()); | ||
| } | ||
|
|
||
| if (!found_minus_one) | ||
| { | ||
| SG_WARNING( | ||
| "%s%s%s::ensure_valid): Not a two class labeling - no negatively labeled examples found\n", | ||
| context ? context : "", context ? ": " : "", get_name()); | ||
| } | ||
| } | ||
|
|
||
| ELabelType CBinaryLabels::get_label_type() const | ||
| { | ||
| return LT_BINARY; | ||
| } | ||
|
|
||
| void CBinaryLabels::scores_to_probabilities(float64_t a, float64_t b) | ||
| { | ||
| SG_DEBUG("entering CBinaryLabels::scores_to_probabilities()\n") | ||
|
|
||
| REQUIRE(m_current_values.vector, "%s::scores_to_probabilities() requires " | ||
| "values vector!\n", get_name()); | ||
|
|
||
| if (a==0 && b==0) | ||
| { | ||
| CStatistics::SigmoidParamters params= | ||
| CStatistics::fit_sigmoid(m_current_values); | ||
| a=params.a; | ||
| b=params.b; | ||
| } | ||
|
|
||
| SG_DEBUG("using sigmoid: a=%f, b=%f\n", a, b) | ||
|
|
||
| /* now the sigmoid is fitted, convert all values to probabilities */ | ||
| for (index_t i=0; i<m_current_values.vlen; ++i) | ||
| { | ||
| float64_t fApB=m_current_values[i]*a+b; | ||
| m_current_values[i]=fApB>=0 ? CMath::exp(-fApB)/(1.0+CMath::exp(-fApB)) : | ||
| 1.0/(1+CMath::exp(fApB)); | ||
| } | ||
|
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||
| SG_DEBUG("leaving CBinaryLabels::scores_to_probabilities()\n") | ||
| } | ||
| /* | ||
| * 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) 1999-2008 Gunnar Raetsch | ||
| * Written (W) 2011-2012 Heiko Strathmann | ||
| * Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society | ||
| */ | ||
|
|
||
| #include <shogun/labels/DenseLabels.h> | ||
| #include <shogun/labels/BinaryLabels.h> | ||
| #include <shogun/mathematics/Statistics.h> | ||
| #include <shogun/lib/SGVector.h> | ||
|
|
||
| using namespace shogun; | ||
|
|
||
| CBinaryLabels::CBinaryLabels() : CDenseLabels() | ||
| { | ||
| } | ||
|
|
||
| CBinaryLabels::CBinaryLabels(int32_t num_labels) : CDenseLabels(num_labels) | ||
| { | ||
| } | ||
|
|
||
| #if !defined(SWIGJAVA) && !defined(SWIGCSHARP) | ||
| CBinaryLabels::CBinaryLabels(SGVector<int32_t> src) : CDenseLabels() | ||
| { | ||
| SGVector<float64_t> values(src.vlen); | ||
| for (int32_t i = 0; i < values.vlen; i++) | ||
| { | ||
| values[i] = src[i]; | ||
| } | ||
| set_int_labels(src); | ||
| set_values(values); | ||
| } | ||
|
|
||
| CBinaryLabels::CBinaryLabels(SGVector<int64_t> src) : CDenseLabels() | ||
| { | ||
| SGVector<float64_t> values(src.vlen); | ||
| for (int32_t i = 0; i < values.vlen; i++) | ||
| { | ||
| values[i] = src[i]; | ||
| } | ||
| set_int_labels(src); | ||
| set_values(values); | ||
| } | ||
| #endif | ||
|
|
||
| CBinaryLabels::CBinaryLabels(SGVector<float64_t> src, float64_t threshold) : CDenseLabels() | ||
| { | ||
| SGVector<float64_t> labels(src.vlen); | ||
| for (int32_t i = 0; i < labels.vlen; i++) | ||
| { | ||
| labels[i] = src[i] + threshold >= 0 ? +1.0 : -1.0; | ||
| } | ||
| set_labels(labels); | ||
| set_values(src); | ||
| } | ||
|
|
||
| CBinaryLabels::CBinaryLabels(CFile * loader) : CDenseLabels(loader) | ||
| { | ||
| } | ||
|
|
||
| void CBinaryLabels::ensure_valid(const char * context) | ||
| { | ||
| CDenseLabels::ensure_valid(context); | ||
| bool found_plus_one = false; | ||
| bool found_minus_one = false; | ||
|
|
||
| int32_t subset_size = get_num_labels(); | ||
| for (int32_t i = 0; i < subset_size; i++) | ||
| { | ||
| int32_t real_i = m_subset_stack->subset_idx_conversion(i); | ||
| if (m_labels[real_i] == +1.0) | ||
| { | ||
| found_plus_one = true; | ||
| } | ||
| else if (m_labels[real_i] == -1.0) | ||
| { | ||
| found_minus_one = true; | ||
| } | ||
| else | ||
| { | ||
| SG_ERROR( | ||
| "%s%s%s::ensure_valid(): Not a two class labeling label[%d]=%f (only +1/-1 " | ||
| "allowed)\n", context ? context : "", | ||
| context ? ": " : "", get_name(), i, m_labels[real_i]); | ||
| } | ||
| } | ||
|
|
||
| if (!found_plus_one) | ||
| { | ||
| SG_WARNING( | ||
| "%s%s%s::ensure_valid(): Not a two class labeling - no positively labeled examples found\n", | ||
| context ? context : "", context ? ": " : "", get_name()); | ||
| } | ||
|
|
||
| if (!found_minus_one) | ||
| { | ||
| SG_WARNING( | ||
| "%s%s%s::ensure_valid): Not a two class labeling - no negatively labeled examples found\n", | ||
| context ? context : "", context ? ": " : "", get_name()); | ||
| } | ||
| } | ||
|
|
||
| ELabelType CBinaryLabels::get_label_type() const | ||
| { | ||
| return LT_BINARY; | ||
| } | ||
|
|
||
| void CBinaryLabels::scores_to_probabilities(float64_t a, float64_t b) | ||
| { | ||
| SG_DEBUG("entering CBinaryLabels::scores_to_probabilities()\n") | ||
|
|
||
| REQUIRE(m_current_values.vector, "%s::scores_to_probabilities() requires " | ||
| "values vector!\n", get_name()); | ||
|
|
||
| if (a == 0 && b == 0) | ||
| { | ||
| CStatistics::SigmoidParamters params = | ||
| CStatistics::fit_sigmoid(m_current_values); | ||
| a = params.a; | ||
| b = params.b; | ||
| } | ||
|
|
||
| SG_DEBUG("using sigmoid: a=%f, b=%f\n", a, b) | ||
|
|
||
| /* now the sigmoid is fitted, convert all values to probabilities */ | ||
| for (index_t i = 0; i < m_current_values.vlen; ++i) | ||
| { | ||
| float64_t fApB = m_current_values[i] * a + b; | ||
| m_current_values[i] = fApB >= 0 ? CMath::exp(-fApB) / (1.0 + CMath::exp(-fApB)) : | ||
| 1.0 / (1 + CMath::exp(fApB)); | ||
| } | ||
|
|
||
| SG_DEBUG("leaving CBinaryLabels::scores_to_probabilities()\n") | ||
| } |
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