Split up CLabels into various classes:

CLabels -> CDenseLabels -> CRealLabels -> CBinaryLabels -> CMulticlassLabels -> CRealLabels - put labels under shogun/labels/ - change include paths in all files - CMachine still returns a generic CLabels object in its apply() function - but submachines create customized CRealLabels, CMulticlassLabels etc objects. - all machines now check if their train function is called with matching label type - type of label object can be determined via label->get_label_type() - introduce confidences in labels - introduce set_to_const function in labels
shogun-toolbox · May 20, 2012 · da70cf4 · da70cf4
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diff --git a/src/README.developer b/src/README.developer
@@ -51,7 +51,7 @@ To finally see some action one has to include the appropriate header files,
 e.g. we create some features and a gaussian kernel
 
 
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
 #include <shogun/features/DenseFeatures.h>
 #include <shogun/kernel/GaussianKernel.h>
 #include <shogun/classifier/svm/LibSVM.h>

diff --git a/src/interfaces/modular/Evaluation_includes.i b/src/interfaces/modular/Evaluation_includes.i
@@ -1,5 +1,5 @@
 %{
- #include <shogun/features/Labels.h>
+ #include <shogun/labels/Labels.h>
  #include <shogun/evaluation/Evaluation.h>
  #include <shogun/evaluation/BinaryClassEvaluation.h>
  #include <shogun/evaluation/ClusteringEvaluation.h>

diff --git a/src/interfaces/modular/Features.i b/src/interfaces/modular/Features.i
@@ -33,6 +33,10 @@
 %rename(CombinedFeatures) CCombinedFeatures;
 %rename(CombinedDotFeatures) CCombinedDotFeatures;
 %rename(Labels) CLabels;
+%rename(DenseLabels) CDenseLabels;
+%rename(BinaryLabels) CBinaryLabels;
+%rename(MulticlassLabels) CMulticlassLabels;
+%rename(RegressionLabels) CRegressionLabels;
 %rename(RealFileFeatures) CRealFileFeatures;
 %rename(FKFeatures) CFKFeatures;
 %rename(TOPFeatures) CTOPFeatures;
@@ -356,7 +360,11 @@ namespace shogun
 %include <shogun/features/CombinedFeatures.h>
 %include <shogun/features/CombinedDotFeatures.h>
 
-%include <shogun/features/Labels.h>
+%include <shogun/labels/Labels.h>
+%include <shogun/labels/DenseLabels.h>
+%include <shogun/labels/BinaryLabels.h>
+%include <shogun/labels/MulticlassLabels.h>
+%include <shogun/labels/RealLabels.h>
 %include <shogun/features/RealFileFeatures.h>
 %include <shogun/features/FKFeatures.h>
 %include <shogun/features/TOPFeatures.h>

diff --git a/src/interfaces/modular/Features_includes.i b/src/interfaces/modular/Features_includes.i
@@ -18,7 +18,12 @@
 #include <shogun/features/Alphabet.h>
 #include <shogun/features/CombinedFeatures.h>
 #include <shogun/features/CombinedDotFeatures.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
+#include <shogun/labels/DenseLabels.h>
+#include <shogun/labels/BinaryLabels.h>
+#include <shogun/labels/MulticlassLabels.h>
+#include <shogun/labels/RealLabels.h>
+#include <shogun/features/RealFileFeatures.h>
 #include <shogun/features/RealFileFeatures.h>
 #include <shogun/features/FKFeatures.h>
 #include <shogun/features/TOPFeatures.h>

diff --git a/src/shogun/classifier/AveragedPerceptron.cpp b/src/shogun/classifier/AveragedPerceptron.cpp
@@ -8,8 +8,9 @@
  */
 
 #include <shogun/classifier/AveragedPerceptron.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
 #include <shogun/mathematics/Math.h>
+#include <shogun/labels/BinaryLabels.h>
 
 using namespace shogun;
 
@@ -32,6 +33,8 @@ CAveragedPerceptron::~CAveragedPerceptron()
 bool CAveragedPerceptron::train(CFeatures* data)
 {
 	ASSERT(m_labels);
+	ASSERT(m_labels->get_label_type() == LT_BINARY);
+
 	if (data)
 	{
 		if (!data->has_property(FP_DOT))
@@ -41,7 +44,7 @@ bool CAveragedPerceptron::train(CFeatures* data)
 	ASSERT(features);
 	bool converged=false;
 	int32_t iter=0;
-	SGVector<int32_t> train_labels=m_labels->get_int_labels();
+	SGVector<int32_t> train_labels=((CBinaryLabels*) m_labels)->get_int_labels();
 	int32_t num_feat=features->get_dim_feature_space();
 	int32_t num_vec=features->get_num_vectors();
 

diff --git a/src/shogun/classifier/GaussianNaiveBayes.cpp b/src/shogun/classifier/GaussianNaiveBayes.cpp
@@ -11,7 +11,9 @@
 #include <shogun/classifier/GaussianNaiveBayes.h>
 #include <shogun/machine/Machine.h>
 #include <shogun/features/Features.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
+#include <shogun/labels/RealLabels.h>
+#include <shogun/labels/MulticlassLabels.h>
 #include <shogun/mathematics/Math.h>
 #include <shogun/lib/Signal.h>
 
@@ -71,7 +73,8 @@ bool CGaussianNaiveBayes::train(CFeatures* data)
 
 	// get int labels to train_labels and check length equality
 	ASSERT(m_labels);
-	SGVector<int32_t> train_labels = m_labels->get_int_labels();
+	ASSERT(m_labels->get_label_type() == LT_MULTICLASS);
+	SGVector<int32_t> train_labels = ((CMulticlassLabels*) m_labels)->get_int_labels();
 	ASSERT(m_features->get_num_vectors()==train_labels.vlen);
 
 	// init min_label, max_label and loop variables
@@ -176,7 +179,7 @@ CLabels* CGaussianNaiveBayes::apply()
 	int32_t num_vectors = m_features->get_num_vectors();
 
 	// init result labels
-	CLabels* result = new CLabels(num_vectors);
+	CRealLabels* result = new CRealLabels(num_vectors);
 
 	// classify each example of data
 	SG_PROGRESS(0, 0, num_vectors);

diff --git a/src/shogun/classifier/LDA.cpp b/src/shogun/classifier/LDA.cpp
@@ -14,7 +14,8 @@
 #include <shogun/machine/Machine.h>
 #include <shogun/machine/LinearMachine.h>
 #include <shogun/classifier/LDA.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
+#include <shogun/labels/BinaryLabels.h>
 #include <shogun/mathematics/Math.h>
 #include <shogun/mathematics/lapack.h>
 
@@ -47,7 +48,7 @@ bool CLDA::train_machine(CFeatures* data)
 		set_features((CDotFeatures*) data);
 	}
 	ASSERT(features);
-	SGVector<int32_t> train_labels=m_labels->get_int_labels();
+	SGVector<int32_t> train_labels=((CBinaryLabels*) m_labels)->get_int_labels();
 	ASSERT(train_labels.vector);
 
 	int32_t num_feat=features->get_dim_feature_space();

diff --git a/src/shogun/classifier/LPBoost.cpp b/src/shogun/classifier/LPBoost.cpp
@@ -13,7 +13,7 @@
 #ifdef USE_CPLEX
 
 #include <shogun/classifier/LPBoost.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
 #include <shogun/mathematics/Math.h>
 #include <shogun/mathematics/Cplex.h>
 #include <shogun/lib/DynamicArray.h>

diff --git a/src/shogun/classifier/LPM.cpp b/src/shogun/classifier/LPM.cpp
@@ -13,7 +13,7 @@
 #ifdef USE_CPLEX
 
 #include <shogun/classifier/LPM.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
 #include <shogun/mathematics/Math.h>
 #include <shogun/mathematics/Cplex.h>
 

diff --git a/src/shogun/classifier/NearestCentroid.cpp b/src/shogun/classifier/NearestCentroid.cpp
@@ -8,6 +8,7 @@
  */
 
 #include <shogun/classifier/NearestCentroid.h>
+#include <shogun/labels/MulticlassLabels.h>
 #include <shogun/features/Features.h>
 #include <shogun/features/FeatureTypes.h>
 
@@ -48,6 +49,7 @@ namespace shogun{
 	bool CNearestCentroid::train_machine(CFeatures* data)
 	{
 		ASSERT(m_labels);
+		ASSERT(m_labels->get_label_type() == LT_MULTICLASS);
 		ASSERT(distance);
 		ASSERT( data->get_feature_class() == C_DENSE)
 		if (data)
@@ -61,8 +63,8 @@ namespace shogun{
 			data = distance->get_lhs();
 		}
 		int32_t num_vectors = data->get_num_vectors();
-		int32_t num_classes = m_labels->get_num_classes();
-		int32_t num_feats = ((CDenseFeatures<float64_t>*)data)->get_num_features();
+		int32_t num_classes = ((CMulticlassLabels*) m_labels)->get_num_classes();
+		int32_t num_feats = ((CDenseFeatures<float64_t>*) data)->get_num_features();
 		SGMatrix<float64_t> centroids(num_feats,num_classes);
 		centroids.zero();
 
@@ -79,7 +81,7 @@ namespace shogun{
 		{
 			int32_t current_len;
 			bool current_free;
-			int32_t current_class = m_labels->get_label(idx);
+			int32_t current_class = ((CMulticlassLabels*) m_labels)->get_label(idx);
 			float64_t* target = centroids.matrix + num_feats*current_class;
 			float64_t* current = ((CDenseFeatures<float64_t>*)data)->get_feature_vector(idx,current_len,current_free);
 			CMath::add(target,1.0,target,1.0,current,current_len);

diff --git a/src/shogun/classifier/Perceptron.cpp b/src/shogun/classifier/Perceptron.cpp
@@ -9,7 +9,8 @@
  */
 
 #include <shogun/classifier/Perceptron.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
+#include <shogun/labels/BinaryLabels.h>
 #include <shogun/mathematics/Math.h>
 
 using namespace shogun;
@@ -33,16 +34,19 @@ CPerceptron::~CPerceptron()
 bool CPerceptron::train_machine(CFeatures* data)
 {
 	ASSERT(m_labels);
+	ASSERT(m_labels->get_label_type() == LT_BINARY);
+
 	if (data)
 	{
 		if (!data->has_property(FP_DOT))
 			SG_ERROR("Specified features are not of type CDotFeatures\n");
 		set_features((CDotFeatures*) data);
 	}
+
 	ASSERT(features);
 	bool converged=false;
 	int32_t iter=0;
-	SGVector<int32_t> train_labels=m_labels->get_int_labels();
+	SGVector<int32_t> train_labels=((CBinaryLabels*) m_labels)->get_int_labels();
 	int32_t num_feat=features->get_dim_feature_space();
 	int32_t num_vec=features->get_num_vectors();
 

diff --git a/src/shogun/classifier/PluginEstimate.cpp b/src/shogun/classifier/PluginEstimate.cpp
@@ -11,7 +11,9 @@
 #include <shogun/lib/common.h>
 #include <shogun/io/SGIO.h>
 #include <shogun/features/StringFeatures.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
+#include <shogun/labels/BinaryLabels.h>
+#include <shogun/labels/RealLabels.h>
 #include <shogun/distributions/LinearHMM.h>
 #include <shogun/classifier/PluginEstimate.h>
 
@@ -46,6 +48,7 @@ CPluginEstimate::~CPluginEstimate()
 bool CPluginEstimate::train_machine(CFeatures* data)
 {
 	ASSERT(m_labels);
+	ASSERT(m_labels->get_label_type() == LT_BINARY);
 	if (data)
 	{
 		if (data->get_feature_class() != C_STRING ||
@@ -77,7 +80,7 @@ bool CPluginEstimate::train_machine(CFeatures* data)
 
 	for (int32_t i=0; i<m_labels->get_num_labels(); i++)
 	{
-		if (m_labels->get_label(i) > 0)
+		if (((CBinaryLabels*) m_labels)->get_label(i) > 0)
 			pos_indizes[pos_idx++]=i;
 		else
 			neg_indizes[neg_idx++]=i;
@@ -96,7 +99,7 @@ bool CPluginEstimate::train_machine(CFeatures* data)
 CLabels* CPluginEstimate::apply()
 {
 	ASSERT(features);
-	CLabels* result=new CLabels(features->get_num_vectors());
+	CRealLabels* result=new CRealLabels(features->get_num_vectors());
 	ASSERT(result->get_num_labels()==features->get_num_vectors());
 
 	for (int32_t vec=0; vec<features->get_num_vectors(); vec++)

diff --git a/src/shogun/classifier/PluginEstimate.h b/src/shogun/classifier/PluginEstimate.h
@@ -13,7 +13,7 @@
 
 #include <shogun/machine/Machine.h>
 #include <shogun/features/StringFeatures.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
 #include <shogun/distributions/LinearHMM.h>
 
 namespace shogun

diff --git a/src/shogun/classifier/QDA.cpp b/src/shogun/classifier/QDA.cpp
@@ -14,6 +14,9 @@
 
 #include <shogun/classifier/QDA.h>
 #include <shogun/features/Features.h>
+#include <shogun/labels/Labels.h>
+#include <shogun/labels/RealLabels.h>
+#include <shogun/labels/MulticlassLabels.h>
 #include <shogun/machine/Machine.h>
 #include <shogun/mathematics/Math.h>
 #include <shogun/mathematics/lapack.h>
@@ -120,7 +123,7 @@ CLabels* CQDA::apply()
 			norm2[i + k*num_vecs] *= -0.5;
 		}
 
-	CLabels* out = new CLabels(num_vecs);
+	CRealLabels* out = new CRealLabels(num_vecs);
 
 	for ( i = 0 ; i < num_vecs ; ++i )
 		out->set_label(i, CMath::arg_max(norm2.vector+i, num_vecs, m_num_classes));
@@ -157,13 +160,13 @@ bool CQDA::train_machine(CFeatures* data)
 	}
 	if ( !m_features )
 		SG_ERROR("No features allocated in QDA training\n");
-	SGVector< int32_t > train_labels = m_labels->get_int_labels();
+	SGVector< int32_t > train_labels = ((CMulticlassLabels*) m_labels)->get_int_labels();
 	if ( !train_labels.vector )
 		SG_ERROR("No train_labels allocated in QDA training\n");
 
 	cleanup();
 
-	m_num_classes = m_labels->get_num_classes();
+	m_num_classes = ((CMulticlassLabels*) m_labels)->get_num_classes();
 	m_dim = m_features->get_dim_feature_space();
 	int32_t num_vec  = m_features->get_num_vectors();
 	if ( num_vec != train_labels.vlen )

diff --git a/src/shogun/classifier/SubGradientLPM.cpp b/src/shogun/classifier/SubGradientLPM.cpp
@@ -20,7 +20,7 @@
 #include <shogun/classifier/SubGradientLPM.h>
 #include <shogun/classifier/svm/QPBSVMLib.h>
 #include <shogun/features/DotFeatures.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
 
 using namespace shogun;
 

diff --git a/src/shogun/classifier/SubGradientLPM.h b/src/shogun/classifier/SubGradientLPM.h
@@ -21,7 +21,7 @@
 
 #include <shogun/machine/LinearMachine.h>
 #include <shogun/features/Features.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
 
 namespace shogun
 {

diff --git a/src/shogun/classifier/mkl/MKLClassification.cpp b/src/shogun/classifier/mkl/MKLClassification.cpp
@@ -34,5 +34,5 @@ float64_t CMKLClassification::compute_sum_alpha()
 
 void CMKLClassification::init_training()
 {
-	ASSERT(m_labels && m_labels->get_num_labels() && m_labels->is_two_class_labeling());
+	ASSERT(m_labels && m_labels->get_num_labels() && m_labels->get_label_type() == LT_BINARY);
 }
diff --git a/src/shogun/classifier/mkl/MKLMulticlass.cpp b/src/shogun/classifier/mkl/MKLMulticlass.cpp
@@ -11,6 +11,7 @@
 #include <shogun/multiclass/MulticlassOneVsRestStrategy.h>
 #include <shogun/classifier/mkl/MKLMulticlass.h>
 #include <shogun/io/SGIO.h>
+#include <shogun/labels/MulticlassLabels.h>
 
 using namespace shogun;
 
@@ -239,13 +240,13 @@ void CMKLMulticlass::addingweightsstep( const std::vector<float64_t> &
 float64_t CMKLMulticlass::getsumofsignfreealphas()
 {
 	std::vector<int> trainlabels2(m_labels->get_num_labels());
-	SGVector<int32_t> lab=m_labels->get_int_labels();
+	SGVector<int32_t> lab=((CMulticlassLabels*) m_labels)->get_int_labels();
 	std::copy(lab.vector,lab.vector+lab.vlen, trainlabels2.begin());
 
 	ASSERT (trainlabels2.size()>0);
 	float64_t sum=0;
 
-	for (int32_t nc=0; nc< m_labels->get_num_classes();++nc)
+	for (int32_t nc=0; nc< ((CMulticlassLabels*) m_labels)->get_num_classes();++nc)
 	{
 		CSVM * sm=svm->get_svm(nc);
 
@@ -261,7 +262,7 @@ float64_t CMKLMulticlass::getsumofsignfreealphas()
 
 	for (size_t lb=0; lb< trainlabels2.size();++lb)
 	{
-		for (int32_t nc=0; nc< m_labels->get_num_classes();++nc)
+		for (int32_t nc=0; nc< ((CMulticlassLabels*) m_labels)->get_num_classes();++nc)
 		{
 			CSVM * sm=svm->get_svm(nc);
 
@@ -289,7 +290,7 @@ float64_t CMKLMulticlass::getsquarenormofprimalcoefficients(
 
 	float64_t tmp=0;
 
-	for (int32_t classindex=0; classindex< m_labels->get_num_classes();
+	for (int32_t classindex=0; classindex< ((CMulticlassLabels*) m_labels)->get_num_classes();
 			++classindex)
 	{
 		CSVM * sm=svm->get_svm(classindex);
@@ -320,9 +321,10 @@ float64_t CMKLMulticlass::getsquarenormofprimalcoefficients(
 
 bool CMKLMulticlass::train_machine(CFeatures* data)
 {
-	int numcl=m_labels->get_num_classes();
 	ASSERT(m_kernel);
 	ASSERT(m_labels && m_labels->get_num_labels());
+	ASSERT(m_labels->get_label_type() == LT_MULTICLASS);
+	int numcl=((CMulticlassLabels*) m_labels)->get_num_classes();
 
 	if (data)
 	{

diff --git a/src/shogun/classifier/svm/CPLEXSVM.cpp b/src/shogun/classifier/svm/CPLEXSVM.cpp
@@ -15,7 +15,7 @@
 #include <shogun/io/SGIO.h>
 #include <shogun/mathematics/Math.h>
 #include <shogun/mathematics/Cplex.h>
-#include <shogun/features/Labels.h>
+#include <shogun/labels/Labels.h>
 
 using namespace shogun;