use appropriate label types for ruby modular

shogun-toolbox · May 26, 2012 · 156a436 · 156a436
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commit 156a436
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Showing 6 changed files with 8 additions and 8 deletions.
diff --git a/examples/undocumented/ruby_modular/classifier_custom_kernel_modular.rb b/examples/undocumented/ruby_modular/classifier_custom_kernel_modular.rb
@@ -15,7 +15,7 @@ def classifier_custom_kernel_modular(c=1,dim=7)
 
 	kernel=Modshogun::CustomKernel.new
 	kernel.set_full_kernel_matrix_from_full(data)
-	labels=Modshogun::Labels.new(lab)
+	labels=Modshogun::BinaryLabels.new(lab)
 	svm=Modshogun::LibSVM.new(c, kernel, labels)
 	svm.train()
 	predictions =svm.apply() 

diff --git a/examples/undocumented/ruby_modular/classifier_libsvm_minimal_modular.rb b/examples/undocumented/ruby_modular/classifier_libsvm_minimal_modular.rb
@@ -23,9 +23,9 @@
 kernel = Modshogun::GaussianKernel.new feats_train, feats_train, @width
 
 puts "labeling stuff"
-labels = Modshogun::Labels.new
+labels = Modshogun::BinaryLabels.new
 labels.set_labels trainlab
-svm = Modshogun::LibSVM.new C, kernel, labels
+svm = Modshogun::BinaryLibSVM.new C, kernel, labels
 svm.train
 
 puts "the grand finale"

diff --git a/examples/undocumented/ruby_modular/features_io_modular.rb b/examples/undocumented/ruby_modular/features_io_modular.rb
@@ -53,8 +53,8 @@ def features_io_modular(fm_train_real, label_train_twoclass)
 	feats2.load(f)
 	f.close()
 
-	lab=Modshogun::Labels.new([1.0,2.0,3.0])
-	lab2=Modshogun::Labels.new
+	lab=Modshogun::MulticlassLabels.new([0.0,1.0,2.0,3.0])
+	lab2=Modshogun::MulticlassLabels.new
 
 	f=Modshogun::AsciiFile.new("label_train_twoclass.ascii","w")
 	lab.save(f)

diff --git a/examples/undocumented/ruby_modular/kernel_auc_modular.rb b/examples/undocumented/ruby_modular/kernel_auc_modular.rb
@@ -18,7 +18,7 @@ def kernel_auc_modular(fm_train_real=traindat,label_train_real=testdat,width=1.7
 
 # *** 	kernel=AUCKernel(0, subkernel)
 	kernel=Modshogun::AUCKernel.new(0, subkernel)
-	kernel.setup_auc_maximization( Modshogun::Labels.new(label_train_real) )
+	kernel.setup_auc_maximization( Modshogun::BinaryLabels.new(label_train_real) )
 	km_train=kernel.get_kernel_matrix()
 	return kernel
 end

diff --git a/examples/undocumented/ruby_modular/kernel_combined_custom_poly_modular.rb b/examples/undocumented/ruby_modular/kernel_combined_custom_poly_modular.rb
@@ -30,7 +30,7 @@ def kernel_combined_custom_poly_modular(fm_train_real = traindat,fm_test_real =
 
     kernel.init(feats_train, feats_train)
 
-    labels = Modshogun::Labels.new(fm_label_twoclass)
+    labels = Modshogun::BinaryLabels.new(fm_label_twoclass)
     svm = Modshogun::LibSVM.new(1.0, kernel, labels)
     svm.train()
 

diff --git a/examples/undocumented/ruby_modular/regression_libsvr_modular.rb b/examples/undocumented/ruby_modular/regression_libsvr_modular.rb
@@ -19,7 +19,7 @@ def regression_libsvr_modular(fm_train=traindat,fm_test=testdat,label_train=labe
 	feats_test.set_feature_matrix(fm_test)
 
 	kernel=Modshogun::GaussianKernel.new(feats_train, feats_train, width)
-	labels=Modshogun::Labels.new(label_train)
+	labels=Modshogun::RegressionLabels.new(label_train)
 
 	svr=Modshogun::LibSVR.new(c, tube_epsilon, kernel, labels)
 	svr.set_epsilon(epsilon)