fix lua examples

shogun-toolbox · May 24, 2012 · d4a6596 · d4a6596
1 parent 8b0279c
commit d4a6596
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Showing 6 changed files with 7 additions and 7 deletions.
diff --git a/examples/undocumented/lua_modular/check.sh b/examples/undocumented/lua_modular/check.sh
@@ -2,7 +2,7 @@
 
 rm -f error.log
 
-#export LUA_CPATH=../../../src/interfaces/lua_modular/?.so
+export LUA_CPATH=../../../src/interfaces/lua_modular/?.so
 
 for e in $(ls -1 *.lua | grep -v load.lua)
 do

diff --git a/examples/undocumented/lua_modular/classifier_averaged_perceptron_modular.lua b/examples/undocumented/lua_modular/classifier_averaged_perceptron_modular.lua
@@ -12,7 +12,7 @@ function classifier_averaged_perceptron_modular (fm_train_real,fm_test_real,labe
 	feats_train=modshogun.RealFeatures(fm_train_real)
 	feats_test=modshogun.RealFeatures(fm_test_real)
 
-	labels=modshogun.Labels(label_train_twoclass)
+	labels=modshogun.BinaryLabels(label_train_twoclass)
 
 	perceptron=modshogun.AveragedPerceptron(feats_train, labels)
 	perceptron:set_learn_rate(learn_rate)

diff --git a/examples/undocumented/lua_modular/classifier_libsvm_minimal_modular.lua b/examples/undocumented/lua_modular/classifier_libsvm_minimal_modular.lua
@@ -57,7 +57,7 @@ feats_train=modshogun.RealFeatures(traindata_real)
 feats_test=modshogun.RealFeatures(testdata_real)
 kernel=modshogun.GaussianKernel(feats_train, feats_train, width)
 
-labels=modshogun.Labels(trainlab)
+labels=modshogun.BinaryLabels(trainlab)
 svm=modshogun.LibSVM(C, kernel, labels)
 svm:train()
 

diff --git a/examples/undocumented/lua_modular/evaluation_contingencytableevaluation_modular.lua b/examples/undocumented/lua_modular/evaluation_contingencytableevaluation_modular.lua
@@ -12,8 +12,8 @@ parameter_list = {{ground_truth,predicted}}
 
 function evaluation_contingencytableevaluation_modular(ground_truth, predicted)
 
-	ground_truth_labels = modshogun.Labels(ground_truth)
-	predicted_labels = modshogun.Labels(predicted)
+	ground_truth_labels = modshogun.BinaryLabels(ground_truth)
+	predicted_labels = modshogun.BinaryLabels(predicted)
 
 	base_evaluator = modshogun.ContingencyTableEvaluation()
 	base_evaluator:evaluate(predicted_labels,ground_truth_labels)

diff --git a/examples/undocumented/lua_modular/regression_krr_modular.lua b/examples/undocumented/lua_modular/regression_krr_modular.lua
@@ -14,7 +14,7 @@ function regression_krr_modular (fm_train,fm_test,label_train,width,tau)
 
 	kernel=modshogun.GaussianKernel(feats_train, feats_train, width)
 
-	labels=modshogun.Labels(label_train)
+	labels=modshogun.RegressionLabels(label_train)
 
 	krr=modshogun.KernelRidgeRegression(tau, kernel, labels)
 	krr:train(feats_train)

diff --git a/examples/undocumented/lua_modular/serialization_complex_example.lua b/examples/undocumented/lua_modular/serialization_complex_example.lua
@@ -64,7 +64,7 @@ function serialization_complex_example(num, dist, dim, C, width)
 	feats=modshogun.RealFeatures(data)
 	kernel=modshogun.GaussianKernel(feats, feats, width)
 
-	labels=modshogun.Labels(lab)
+	labels=modshogun.MulticlassLabels(lab)
 
 	svm = modshogun.GMNPSVM(C, kernel, labels)