Merge pull request #932 from karlnapf/master

removed parameter registration for multiclass labels again

examples/undocumented/python_modular/evaluation_clustering.py

@@ -27,11 +27,9 @@ def prepare_data():
 
 def run_clustering(data, k):
 	from shogun.Clustering import KMeans
-	from shogun.Mathematics import Math_init_random
 	from shogun.Distance import EuclideanDistance
 	from shogun.Features import RealFeatures
 
-	Math_init_random(42)
 	fea = RealFeatures(data)
 	distance = EuclideanDistance(fea, fea)
 	kmeans=KMeans(k, distance)
@@ -58,6 +56,11 @@ def assign_labels(data, centroids, ncenters):
 def evaluation_clustering (features=fea, ground_truth=gnd_raw, ncenters=10):
 	from shogun.Evaluation import ClusteringAccuracy, ClusteringMutualInformation
 	from shogun.Features import MulticlassLabels
+	from shogun.Mathematics import Math
+
+	# reproducable results
+	Math.init_random(1)
+
 	centroids = run_clustering(features, ncenters)
 	gnd_hat = assign_labels(features, centroids, ncenters)
 	gnd = MulticlassLabels(ground_truth)
@@ -66,13 +69,15 @@ def evaluation_clustering (features=fea, ground_truth=gnd_raw, ncenters=10):
 	AccuracyEval.best_map(gnd_hat, gnd)
 
 	accuracy = AccuracyEval.evaluate(gnd_hat, gnd)
-	#print(('Clustering accuracy = %.4f' % accuracy))
+	print(('Clustering accuracy = %.4f' % accuracy))
 
 	MIEval = ClusteringMutualInformation()
 	mutual_info = MIEval.evaluate(gnd_hat, gnd)
-	#print(('Clustering mutual information = %.4f' % mutual_info))
+	print(('Clustering mutual information = %.4f' % mutual_info))
 
-	return gnd, gnd_hat, accuracy, MIEval, mutual_info
+	# TODO mutual information does not work with serialization
+	#return gnd, gnd_hat, accuracy, MIEval, mutual_info
+	return gnd, gnd_hat, accuracy
 
 if __name__ == '__main__':
 	print('Evaluation Clustering')

src/shogun/labels/MulticlassLabels.cpp

@@ -1,6 +1,7 @@
 #include <shogun/labels/DenseLabels.h>
 #include <shogun/labels/BinaryLabels.h>
 #include <shogun/labels/MulticlassLabels.h>
+#include <shogun/base/ParameterMap.h>
 
 using namespace shogun;
 
@@ -31,13 +32,17 @@ CMulticlassLabels::~CMulticlassLabels()
 
 void CMulticlassLabels::init()
 {
-	SG_ADD(&m_multiclass_confidences, "multiclass_confidences", "Vectors of "
-			"multiclass confidences", MS_NOT_AVAILABLE);
+	/* for this to work, migration has to be fixed */
+//	SG_ADD(&m_multiclass_confidences, "multiclass_confidences", "Vectors of "
+//			"multiclass confidences", MS_NOT_AVAILABLE);
+
+//	m_parameter_map->finalize_map();
 
 	m_multiclass_confidences=SGMatrix<float64_t>();
 }
 
-void CMulticlassLabels::set_multiclass_confidences(int32_t i, SGVector<float64_t> confidences)
+void CMulticlassLabels::set_multiclass_confidences(int32_t i,
+		SGVector<float64_t> confidences)
 {
 	REQUIRE(confidences.size()==m_multiclass_confidences.num_rows,
 			"%s::set_multiclass_confidences(): Length of confidences should "
@@ -70,7 +75,7 @@ CMulticlassLabels* CMulticlassLabels::obtain_from_generic(CLabels* base_labels)
 	if (!base_labels)
 		return NULL;
 
-	if(base_labels->get_label_type()!=LT_MULTICLASS)
+	if (base_labels->get_label_type()!=LT_MULTICLASS)
 	{
 		SG_SERROR("CMulticlassLabels::base_labels is of wrong type \"%s\"!\n",
 				base_labels->get_name());

src/shogun/machine/KernelMachine.cpp

@@ -690,10 +690,13 @@ void CKernelMachine::init()
 			MS_NOT_AVAILABLE);
 	SG_ADD(&m_svs, "m_svs", "Number of ``support vectors''.", MS_NOT_AVAILABLE);
 
+	/* new parameter from param version 0 to 1 */
 	m_parameter_map->put(
 		new SGParamInfo("custom_kernel", CT_SCALAR, ST_NONE, PT_SGOBJECT, 1),
 		new SGParamInfo()
 	);
+
+	/* new parameter from param version 0 to 1 */
 	m_parameter_map->put(
 		new SGParamInfo("kernel_backup", CT_SCALAR, ST_NONE, PT_SGOBJECT, 1),
 		new SGParamInfo()