Fixed GaussianProcessRegression

shogun-toolbox · May 22, 2012 · 9eb2a83 · 9eb2a83
1 parent b6a6727
commit 9eb2a83
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Showing 3 changed files with 9 additions and 9 deletions.
diff --git a/examples/undocumented/python_modular/regression_gaussian_process_modular.py b/examples/undocumented/python_modular/regression_gaussian_process_modular.py
@@ -25,6 +25,6 @@
 labels=BinaryLabels(trainlab);
 gp=GaussianProcessRegression(1.0, kernel, feats_train, labels);
 gp.train(feats_train);
-out=gp.apply(feats_test).get_labels();
+out=gp.apply_regression(feats_test).get_labels();
 testerr=mean(sign(out)!=testlab)
 print(testerr)
diff --git a/src/shogun/regression/GaussianProcessRegression.cpp b/src/shogun/regression/GaussianProcessRegression.cpp
@@ -52,7 +52,7 @@ void CGaussianProcessRegression::init()
 	SG_ADD(&m_sigma, "sigma", "Sigma.", MS_AVAILABLE);
 }
 
-CLabels* CGaussianProcessRegression::mean_prediction(CFeatures* data)
+CRegressionLabels* CGaussianProcessRegression::mean_prediction(CFeatures* data)
 {
 	if (!kernel)
 		SG_ERROR( "No kernel assigned!\n");
@@ -79,7 +79,7 @@ CLabels* CGaussianProcessRegression::mean_prediction(CFeatures* data)
 	return result;
 }
 
-CLabels* CGaussianProcessRegression::apply(CFeatures* data)
+CRegressionLabels* CGaussianProcessRegression::apply_regression(CFeatures* data)
 {
 	if (data)
 	{

diff --git a/src/shogun/regression/GaussianProcessRegression.h b/src/shogun/regression/GaussianProcessRegression.h
@@ -115,7 +115,7 @@ class CGaussianProcessRegression : public CMachine
 		* @param data (test)data to be classified
 		* @return classified labels
 		*/
-		virtual CLabels* apply(CFeatures* data=NULL);
+		virtual CRegressionLabels* apply_regression(CFeatures* data=NULL);
 
 		/** get classifier type
 		*
@@ -144,19 +144,19 @@ class CGaussianProcessRegression : public CMachine
 		 */
 		virtual bool train_machine(CFeatures* data=NULL);
 	private:
-	  	
+
 		/** function for initialization*/
 		void init();
-		
+
 		/** apply mean prediction from data
 		*
 		* @param data (test)data to be classified
 		* @return classified labels
 		*/
-		virtual CLabels* mean_prediction(CFeatures* data);
-				
+		virtual CRegressionLabels* mean_prediction(CFeatures* data);
+
 	private:
-				
+
 		/** Observation noise alpha */
 		float64_t m_sigma;