Merge pull request #735 from karlnapf/master

new cross-validation output system
shogun-toolbox · Aug 17, 2012 · 3103008 · 3103008
2 parents 9bcdbb0 + 0b1bac4
commit 3103008
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diff --git a/examples/undocumented/libshogun/classifier_libsvm.cpp b/examples/undocumented/libshogun/classifier_libsvm.cpp
@@ -5,99 +5,105 @@
  * (at your option) any later version.
  *
  * Written (W) 2008-2009 Soeren Sonnenburg
+ * Written (W) 2012 Heiko Strathmann
  * Copyright (C) 2008-2009 Fraunhofer Institute FIRST and Max Planck Society
  */
 #include <shogun/kernel/GaussianKernel.h>
 #include <shogun/labels/BinaryLabels.h>
 #include <shogun/features/DenseFeatures.h>
 #include <shogun/classifier/svm/LibSVM.h>
-#include <shogun/mathematics/Math.h>
-#include <shogun/lib/common.h>
-#include <shogun/base/init.h>
-
-#include <stdlib.h>
-#include <stdio.h>
 
 using namespace shogun;
 
-#define NUM 100
-#define DIMS 2
-#define DIST 0.5
-
-float64_t* lab;
-SGMatrix<float64_t> feat;
-
-void gen_rand_data()
+void gen_rand_data(SGVector<float64_t> lab, SGMatrix<float64_t> feat,
+		float64_t dist)
 {
-	lab=SG_MALLOC(float64_t, NUM);
-	feat=SGMatrix<float64_t>(DIMS, NUM);
+	index_t dims=feat.num_rows;
+	index_t num=lab.vlen;
 
-	for (int32_t i=0; i<NUM; i++)
+	for (int32_t i=0; i<num; i++)
 	{
-		if (i<NUM/2)
+		if (i<num/2)
 		{
 			lab[i]=-1.0;
 
-			for (int32_t j=0; j<DIMS; j++)
-				feat.matrix[i*DIMS+j]=CMath::random(0.0,1.0)+DIST;
+			for (int32_t j=0; j<dims; j++)
+				feat(j, i)=CMath::random(0.0, 1.0)+dist;
 		}
 		else
 		{
 			lab[i]=1.0;
 
-			for (int32_t j=0; j<DIMS; j++)
-				feat.matrix[i*DIMS+j]=CMath::random(0.0,1.0)-DIST;
+			for (int32_t j=0; j<dims; j++)
+				feat(j, i)=CMath::random(0.0, 1.0)-dist;
 		}
 	}
-	SGVector<float64_t>::display_vector(lab,NUM);
-	SGMatrix<float64_t>::display_matrix(feat.matrix,DIMS, NUM);
+	lab.display_vector("lab");
+	feat.display_matrix("feat");
 }
 
-int main()
+void test_libsvm()
 {
-
 	const int32_t feature_cache=0;
 	const int32_t kernel_cache=0;
 	const float64_t rbf_width=10;
 	const float64_t svm_C=10;
 	const float64_t svm_eps=0.001;
 
-	init_shogun();
+	index_t num=100;
+	index_t dims=2;
+	float64_t dist=0.5;
 
-	gen_rand_data();
+	SGVector<float64_t> lab(num);
+	SGMatrix<float64_t> feat(dims, num);
+
+	gen_rand_data(lab, feat, dist);
 
 	// create train labels
-	CLabels* labels=new CBinaryLabels(SGVector<float64_t>(lab, NUM));
+	CLabels* labels=new CBinaryLabels(lab);
 
 	// create train features
-	CDenseFeatures<float64_t>* features = new CDenseFeatures<float64_t>(feature_cache);
+	CDenseFeatures<float64_t>* features=new CDenseFeatures<float64_t>(
+			feature_cache);
 	SG_REF(features);
 	features->set_feature_matrix(feat);
 
 	// create gaussian kernel
-	CGaussianKernel* kernel = new CGaussianKernel(kernel_cache, rbf_width);
+	CGaussianKernel* kernel=new CGaussianKernel(kernel_cache, rbf_width);
 	SG_REF(kernel);
 	kernel->init(features, features);
 
 	// create svm via libsvm and train
-	CLibSVM* svm = new CLibSVM(svm_C, kernel, labels);
+	CLibSVM* svm=new CLibSVM(svm_C, kernel, labels);
 	SG_REF(svm);
 	svm->set_epsilon(svm_eps);
 	svm->train();
 
-	printf("num_sv:%d b:%f\n", svm->get_num_support_vectors(), svm->get_bias());
+	SG_SPRINT("num_sv:%d b:%f\n", svm->get_num_support_vectors(),
+			svm->get_bias());
 
 	// classify + display output
 	CBinaryLabels* out_labels=CBinaryLabels::obtain_from_generic(svm->apply());
 
-	for (int32_t i=0; i<NUM; i++)
-		printf("out[%d]=%f (%f)\n", i, out_labels->get_label(i), out_labels->get_confidence(i));
+	for (int32_t i=0; i<num; i++)
+	{
+		SG_SPRINT("out[%d]=%f (%f)\n", i, out_labels->get_label(i),
+				out_labels->get_confidence(i));
+	}
 
 	SG_UNREF(out_labels);
 	SG_UNREF(kernel);
 	SG_UNREF(features);
 	SG_UNREF(svm);
+}
+
+int main()
+{
+	init_shogun();
+
+	test_libsvm();
 
 	exit_shogun();
 	return 0;
 }
+
diff --git a/examples/undocumented/libshogun/evaluation_cross_validation_classification.cpp b/examples/undocumented/libshogun/evaluation_cross_validation_classification.cpp
@@ -108,8 +108,8 @@ void test_cross_validation()
 	cross->set_conf_int_alpha(0.05);
 
 	/* actual evaluation */
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
-	
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
+
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
 		SG_SERROR("Evaluation result is not of type CrossValidationResult!");
 

diff --git a/examples/undocumented/libshogun/evaluation_cross_validation_locked_comparison.cpp b/examples/undocumented/libshogun/evaluation_cross_validation_locked_comparison.cpp
@@ -103,7 +103,7 @@ void test_cross_validation()
 	cross->set_num_runs(5);
 	cross->set_conf_int_alpha(0.05);
 
-	CrossValidationResult* tmp;
+	CCrossValidationResult* tmp;
 	/* no locking */
 	index_t repetitions=5;
 	SG_SPRINT("unlocked x-val\n");
@@ -113,7 +113,7 @@ void test_cross_validation()
 	time.start();
 	for (index_t i=0; i<repetitions; ++i)
 	{
-		tmp = (CrossValidationResult*)cross->evaluate();
+		tmp = (CCrossValidationResult*)cross->evaluate();
 		SG_UNREF(tmp);
 	}
 
@@ -127,7 +127,7 @@ void test_cross_validation()
 
 	for (index_t i=0; i<repetitions; ++i)
         {
-                tmp = (CrossValidationResult*)cross->evaluate();
+                tmp = (CCrossValidationResult*)cross->evaluate();
                 SG_UNREF(tmp);
         }
 
@@ -141,7 +141,7 @@ void test_cross_validation()
 
         for (index_t i=0; i<repetitions; ++i)
         {
-                tmp = (CrossValidationResult*)cross->evaluate();
+                tmp = (CCrossValidationResult*)cross->evaluate();
                 SG_UNREF(tmp);
         }
 

diff --git a/examples/undocumented/libshogun/evaluation_cross_validation_multiclass.cpp b/examples/undocumented/libshogun/evaluation_cross_validation_multiclass.cpp
@@ -122,10 +122,10 @@ void test_cross_validation()
 	cross->set_conf_int_alpha(0.05);
 
 	/* actual evaluation */
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
 
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
-		SG_SERROR("Evaluation result is not of type CrossValidationResult!");
+		SG_SERROR("Evaluation result is not of type CCrossValidationResult!");
 
 	result->print_result();
 

diff --git a/examples/undocumented/libshogun/evaluation_cross_validation_multiclass_mkl.cpp b/examples/undocumented/libshogun/evaluation_cross_validation_multiclass_mkl.cpp
@@ -123,7 +123,7 @@ void test_multiclass_mkl_cv()
 	cross->set_conf_int_alpha(0.05);
 
 	/* perform x-val and print result */
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
 	SG_SPRINT("mean of %d %d-fold x-val runs: %f\n", n_runs, n_folds,
 			result->mean);
 

diff --git a/examples/undocumented/libshogun/evaluation_cross_validation_regression.cpp b/examples/undocumented/libshogun/evaluation_cross_validation_regression.cpp
@@ -95,10 +95,10 @@ void test_cross_validation()
 	cross->set_conf_int_alpha(0.05);
 
 	/* actual evaluation */
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
 
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
-		SG_SERROR("Evaluation result is not of type CrossValidationResult!");
+		SG_SERROR("Evaluation result is not of type CCrossValidationResult!");
 
 	SG_SPRINT("cross_validation estimate:\n");
 	result->print_result();

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_kernel.cpp b/examples/undocumented/libshogun/modelselection_grid_search_kernel.cpp
@@ -153,10 +153,10 @@ int main(int argc, char **argv)
 	/* larger number of runs to have tighter confidence intervals */
 	cross->set_num_runs(10);
 	cross->set_conf_int_alpha(0.01);
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
 
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
-		SG_SERROR("Evaluation result is not of type CrossValidationResult!");
+		SG_SERROR("Evaluation result is not of type CCrossValidationResult!");
 
 	SG_SPRINT("result: ");
 	result->print_result();
@@ -167,10 +167,10 @@ int main(int argc, char **argv)
 	best_combination=grid_search->select_model(print_state);
 	best_combination->apply_to_machine(classifier);
 	SG_UNREF(result);
-	result=(CrossValidationResult*)cross->evaluate();
+	result=(CCrossValidationResult*)cross->evaluate();
 
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
-		SG_SERROR("Evaluation result is not of type CrossValidationResult!");
+		SG_SERROR("Evaluation result is not of type CCrossValidationResult!");
 
 	SG_SPRINT("result (unlocked): ");
 

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_krr.cpp b/examples/undocumented/libshogun/modelselection_grid_search_krr.cpp
@@ -139,10 +139,10 @@ void test_cross_validation()
 	/* larger number of runs to have tighter confidence intervals */
 	cross->set_num_runs(10);
 	cross->set_conf_int_alpha(0.01);
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
 
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
-		SG_SERROR("Evaluation result is not of type CrossValidationResult!");
+		SG_SERROR("Evaluation result is not of type CCrossValidationResult!");
 
 	SG_SPRINT("result: ");
 	result->print_result();

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_linear.cpp b/examples/undocumented/libshogun/modelselection_grid_search_linear.cpp
@@ -98,10 +98,10 @@ int main(int argc, char **argv)
 	best_combination->print_tree();
 
 	best_combination->apply_to_machine(classifier);
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
 
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
-		SG_SERROR("Evaluation result is not of type CrossValidationResult!");
+		SG_SERROR("Evaluation result is not of type CCrossValidationResult!");
 
 	result->print_result();
 

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_mkl.cpp b/examples/undocumented/libshogun/modelselection_grid_search_mkl.cpp
@@ -138,10 +138,10 @@ int main(int argc, char **argv)
 	/* larger number of runs to have tighter confidence intervals */
 	cross->set_num_runs(10);
 	cross->set_conf_int_alpha(0.01);
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
 
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
-		SG_ERROR("Evaluation result is not of type CrossValidationResult!");
+		SG_ERROR("Evaluation result is not of type CCrossValidationResult!");
 
 	SG_SPRINT("result: ");
 	result.print_result();

diff --git a/examples/undocumented/libshogun/modelselection_grid_search_string_kernel.cpp b/examples/undocumented/libshogun/modelselection_grid_search_string_kernel.cpp
@@ -146,10 +146,10 @@ int main(int argc, char **argv)
 	cross->set_num_runs(10);
 	cross->set_conf_int_alpha(0.01);
 	classifier->data_lock(labels, features);
-	CrossValidationResult* result=(CrossValidationResult*)cross->evaluate();
+	CCrossValidationResult* result=(CCrossValidationResult*)cross->evaluate();
 
 	if (result->get_result_type() != CROSSVALIDATION_RESULT)
-		SG_SERROR("Evaluation result is not of type CrossValidationResult!");
+		SG_SERROR("Evaluation result is not of type CCrossValidationResult!");
 
 	SG_SPRINT("result: ");
 	result->print_result();

diff --git a/src/interfaces/modular/Evaluation.i b/src/interfaces/modular/Evaluation.i
@@ -43,7 +43,8 @@
 %rename(GradientCriterion) CGradientCriterion;
 %rename(GradientEvaluation) CGradientEvaluation;
 %rename(MulticlassOVREvaluation) CMulticlassOVREvaluation;
-
+%rename(CrossValidationOutput) CCMulticlassOVREvaluation;
+%rename(CrossValidationResult) CCrossValidationResult;
 
 
 /* Include Class Headers to make them visible from within the target language */
@@ -70,3 +71,4 @@
 %include <shogun/evaluation/MulticlassOVREvaluation.h>
 %include <shogun/evaluation/StratifiedCrossValidationSplitting.h>
 %include <shogun/evaluation/CrossValidationSplitting.h>
+%include <shogun/evaluation/CrossValidationOutput.h>
diff --git a/src/interfaces/modular/Evaluation_includes.i b/src/interfaces/modular/Evaluation_includes.i
@@ -22,5 +22,6 @@
  #include <shogun/evaluation/SplittingStrategy.h>
  #include <shogun/evaluation/StratifiedCrossValidationSplitting.h>
  #include <shogun/evaluation/CrossValidationSplitting.h>
+ #include <shogun/evaluation/CrossValidationOutput.h>
 %}
 
diff --git a/src/interfaces/modular/ModelSelection.i b/src/interfaces/modular/ModelSelection.i
@@ -8,7 +8,7 @@
  * Copyright (C) 2011 Berlin Institute of Technology and Max-Planck-Society
  */
 
-SERIALIZABLE_DUMMY(shogun::CrossValidationResult);
+SERIALIZABLE_DUMMY(shogun::CCrossValidationResult);
 
 /* These functions return new Objects */
 %newobject *::select_model();
@@ -24,11 +24,9 @@ SERIALIZABLE_DUMMY(shogun::CrossValidationResult);
 %rename(RandomSearchModelSelection) CRandomSearchModelSelection;
 %rename(GradientModelSelection) CGradientModelSelection;
 %rename(ModelSelectionBase) CModelSelection;
-%rename(ModelSelectionOutput) CModelSelectionOutput;
 %rename(ModelSelectionParameters) CModelSelectionParameters;
 %rename(ParameterCombination) CParameterCombination;
 
-%include <shogun/modelselection/ModelSelectionOutput.h>
 %include <shogun/modelselection/ModelSelection.h>
 %include <shogun/modelselection/GridSearchModelSelection.h>
 %include <shogun/modelselection/RandomSearchModelSelection.h>

diff --git a/src/interfaces/modular/ModelSelection_includes.i b/src/interfaces/modular/ModelSelection_includes.i
@@ -1,5 +1,4 @@
 %{
-#include <shogun/modelselection/ModelSelectionOutput.h>
 #include <shogun/modelselection/ModelSelection.h>
 #include <shogun/modelselection/ModelSelectionParameters.h>
 #include <shogun/modelselection/GridSearchModelSelection.h>