Set Default Algorithm Name

guoguibing · guoguibing · commit 25aa3abbfc79 · 2014-06-30T14:18:34.000+08:00
diff --git a/librec/src/main/java/librec/ext/AR.java b/librec/src/main/java/librec/ext/AR.java
@@ -52,9 +52,6 @@ public class AR extends Recommender {
 	public AR(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		// Association rules recommender
-		algoName = "AR";
-
 		// cannot predict ratings, but only order preferences
 		isRankingPred = true;
 	}
diff --git a/librec/src/main/java/librec/ext/NMF.java b/librec/src/main/java/librec/ext/NMF.java
@@ -42,8 +42,6 @@ public class NMF extends IterativeRecommender {
 	public NMF(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "NMF";
-
 		// no need to update learning rate
 		lRate = -1;
 	}
diff --git a/librec/src/main/java/librec/ext/PD.java b/librec/src/main/java/librec/ext/PD.java
@@ -53,8 +53,6 @@ public class PD extends Recommender {
 
 	public PD(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
-
-		algoName = "PD";
 	}
 
 	@Override
diff --git a/librec/src/main/java/librec/ext/PRankD.java b/librec/src/main/java/librec/ext/PRankD.java
@@ -61,7 +61,6 @@ public class PRankD extends RankSGD {
 	public PRankD(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "PRankD";
 		isRankingPred = true;
 	}
 
diff --git a/librec/src/main/java/librec/ext/SlopeOne.java b/librec/src/main/java/librec/ext/SlopeOne.java
@@ -38,8 +38,6 @@ public class SlopeOne extends Recommender {
 
 	public SlopeOne(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
-
-		algoName = "SlopeOne";
 	}
 
 	@Override
diff --git a/librec/src/main/java/librec/intf/Recommender.java b/librec/src/main/java/librec/intf/Recommender.java
@@ -133,6 +133,9 @@ public Recommender(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold)
 		numRates = trainMatrix.size();
 		globalMean = trainMatrix.sum() / numRates;
 
+		// class name as the default algorithm name 
+		algoName = this.getClass().getSimpleName();
+		
 		// fold info
 		foldInfo = fold > 0 ? " fold [" + fold + "]" : "";
 
diff --git a/librec/src/main/java/librec/ranking/BPRMF.java b/librec/src/main/java/librec/ranking/BPRMF.java
@@ -49,7 +49,6 @@ public class BPRMF extends IterativeRecommender {
 	public BPRMF(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "BPRMF";
 		isRankingPred = true;
 		initByNorm = false;
 
diff --git a/librec/src/main/java/librec/ranking/CLiMF.java b/librec/src/main/java/librec/ranking/CLiMF.java
@@ -38,8 +38,6 @@ public class CLiMF extends IterativeRecommender {
 
 	public CLiMF(SparseMatrix rm, SparseMatrix tm, int fold) {
 		super(rm, tm, fold);
-
-		algoName = "CLiMF";
 	}
 
 	@Override
diff --git a/librec/src/main/java/librec/ranking/RankALS.java b/librec/src/main/java/librec/ranking/RankALS.java
@@ -52,7 +52,6 @@ public class RankALS extends IterativeRecommender {
 	public RankALS(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "RankALS";
 		isRankingPred = true;
 	}
 
diff --git a/librec/src/main/java/librec/ranking/RankSGD.java b/librec/src/main/java/librec/ranking/RankSGD.java
@@ -44,7 +44,6 @@ public class RankSGD extends IterativeRecommender {
 	public RankSGD(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "RankSGD";
 		isRankingPred = true;
 	}
 
diff --git a/librec/src/main/java/librec/ranking/WRMF.java b/librec/src/main/java/librec/ranking/WRMF.java
@@ -50,7 +50,6 @@ public class WRMF extends IterativeRecommender {
 	public WRMF(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "WRMF";
 		isRankingPred = true; // item recommendation
 
 		alpha = cf.getDouble("WRMF.alpha");
diff --git a/librec/src/main/java/librec/rating/BiasedMF.java b/librec/src/main/java/librec/rating/BiasedMF.java
@@ -37,8 +37,6 @@ public class BiasedMF extends IterativeRecommender {
 
 	public BiasedMF(SparseMatrix rm, SparseMatrix tm, int fold) {
 		super(rm, tm, fold);
-
-		algoName = "BiasedMF";
 	}
 
 	protected void initModel() {
diff --git a/librec/src/main/java/librec/rating/ItemKNN.java b/librec/src/main/java/librec/rating/ItemKNN.java
@@ -65,7 +65,6 @@ public class ItemKNN extends Recommender {
 	public ItemKNN(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "ItemKNN";
 		knn = cf.getInt("num.neighbors");
 	}
 
diff --git a/librec/src/main/java/librec/rating/PMF.java b/librec/src/main/java/librec/rating/PMF.java
@@ -37,8 +37,6 @@ public class PMF extends IterativeRecommender {
 	public PMF(SparseMatrix rm, SparseMatrix tm, int fold) {
 		super(rm, tm, fold);
 
-		algoName = "PMF";
-
 		// disable bold driver
 		isBoldDriver = false; 
 		
diff --git a/librec/src/main/java/librec/rating/RSTE.java b/librec/src/main/java/librec/rating/RSTE.java
@@ -44,8 +44,6 @@ public class RSTE extends SocialRecommender {
 	public RSTE(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "RSTE";
-
 		initByNorm = false;
 		alpha = cf.getDouble("RSTE.alpha");
 	}
diff --git a/librec/src/main/java/librec/rating/RegSVD.java b/librec/src/main/java/librec/rating/RegSVD.java
@@ -34,8 +34,6 @@ public class RegSVD extends IterativeRecommender {
 
 	public RegSVD(SparseMatrix rm, SparseMatrix tm, int fold) {
 		super(rm, tm, fold);
-
-		algoName = "RegSVD";
 	}
 
 	@Override
diff --git a/librec/src/main/java/librec/rating/SoRec.java b/librec/src/main/java/librec/rating/SoRec.java
@@ -44,7 +44,6 @@ public class SoRec extends SocialRecommender {
 	public SoRec(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "SoRec";
 		initByNorm = false;
 	}
 
diff --git a/librec/src/main/java/librec/rating/SoReg.java b/librec/src/main/java/librec/rating/SoReg.java
@@ -49,7 +49,6 @@ public class SoReg extends SocialRecommender {
 	public SoReg(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "SoReg";
 		initByNorm = false;
 	}
 
diff --git a/librec/src/main/java/librec/rating/SocialMF.java b/librec/src/main/java/librec/rating/SocialMF.java
@@ -36,7 +36,6 @@ public class SocialMF extends SocialRecommender {
 	public SocialMF(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "SocialMF";
 		initByNorm = false;
 	}
 
diff --git a/librec/src/main/java/librec/rating/UserKNN.java b/librec/src/main/java/librec/rating/UserKNN.java
@@ -64,7 +64,6 @@ public class UserKNN extends Recommender {
 	public UserKNN(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {
 		super(trainMatrix, testMatrix, fold);
 
-		algoName = "UserKNN";
 		knn = cf.getInt("num.neighbors");
 	}
 

Original file line number	Diff line number	Diff line change
`@@ -52,9 +52,6 @@ public class AR extends Recommender {`
`52`	`52`	`public AR(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {`
`53`	`53`	`super(trainMatrix, testMatrix, fold);`
`54`	`54`
`55`		`- // Association rules recommender`
`56`		`- algoName = "AR";`
`57`		`-`
`58`	`55`	`// cannot predict ratings, but only order preferences`
`59`	`56`	`isRankingPred = true;`
`60`	`57`	`}`
Original file line number	Diff line number	Diff line change
`@@ -42,8 +42,6 @@ public class NMF extends IterativeRecommender {`
`42`	`42`	`public NMF(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {`
`43`	`43`	`super(trainMatrix, testMatrix, fold);`
`44`	`44`
`45`		`- algoName = "NMF";`
`46`		`-`
`47`	`45`	`// no need to update learning rate`
`48`	`46`	`lRate = -1;`
`49`	`47`	`}`
Original file line number	Diff line number	Diff line change
`@@ -53,8 +53,6 @@ public class PD extends Recommender {`
`53`	`53`
`54`	`54`	`public PD(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {`
`55`	`55`	`super(trainMatrix, testMatrix, fold);`
`56`		`-`
`57`		`- algoName = "PD";`
`58`	`56`	`}`
`59`	`57`
`60`	`58`	`@Override`
Original file line number	Diff line number	Diff line change
`@@ -61,7 +61,6 @@ public class PRankD extends RankSGD {`
`61`	`61`	`public PRankD(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {`
`62`	`62`	`super(trainMatrix, testMatrix, fold);`
`63`	`63`
`64`		`- algoName = "PRankD";`
`65`	`64`	`isRankingPred = true;`
`66`	`65`	`}`
`67`	`66`
Original file line number	Diff line number	Diff line change
`@@ -38,8 +38,6 @@ public class SlopeOne extends Recommender {`
`38`	`38`
`39`	`39`	`public SlopeOne(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {`
`40`	`40`	`super(trainMatrix, testMatrix, fold);`
`41`		`-`
`42`		`- algoName = "SlopeOne";`
`43`	`41`	`}`
`44`	`42`
`45`	`43`	`@Override`
Original file line number	Diff line number	Diff line change
`@@ -38,8 +38,6 @@ public class CLiMF extends IterativeRecommender {`
`38`	`38`
`39`	`39`	`public CLiMF(SparseMatrix rm, SparseMatrix tm, int fold) {`
`40`	`40`	`super(rm, tm, fold);`
`41`		`-`
`42`		`- algoName = "CLiMF";`
`43`	`41`	`}`
`44`	`42`
`45`	`43`	`@Override`
Original file line number	Diff line number	Diff line change
`@@ -52,7 +52,6 @@ public class RankALS extends IterativeRecommender {`
`52`	`52`	`public RankALS(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {`
`53`	`53`	`super(trainMatrix, testMatrix, fold);`
`54`	`54`
`55`		`- algoName = "RankALS";`
`56`	`55`	`isRankingPred = true;`
`57`	`56`	`}`
`58`	`57`
Original file line number	Diff line number	Diff line change
`@@ -44,7 +44,6 @@ public class RankSGD extends IterativeRecommender {`
`44`	`44`	`public RankSGD(SparseMatrix trainMatrix, SparseMatrix testMatrix, int fold) {`
`45`	`45`	`super(trainMatrix, testMatrix, fold);`
`46`	`46`
`47`		`- algoName = "RankSGD";`
`48`	`47`	`isRankingPred = true;`
`49`	`48`	`}`
`50`	`49`