ComputeLoss -> ComputeObjective

zenogantner · Feb 4, 2012 · 4a2d15c · 4a2d15c
1 parent 6e8ee09
commit 4a2d15c
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Showing 18 changed files with 28 additions and 28 deletions.
diff --git a/doc/Changes b/doc/Changes
@@ -9,7 +9,7 @@
 	 - move PredictItems from ItemRecommendation.Extensions to Extensions,
 	   add method ScoreItems
 	 - add interface IFoldInRatingPredictor with extension methods
-	 - IIterativeModel.ComputeLoss(): return float instead of double
+	 - IIterativeModel: double ComputeLoss() => float ComputeObjective()
 	recommenders
 	 - #157: matrix factorization recommenders use float to store the
            latent factors

diff --git a/src/MyMediaLite/IIterativeModel.cs b/src/MyMediaLite/IIterativeModel.cs
@@ -1,4 +1,4 @@
-// Copyright (C) 2010, 2011 Zeno Gantner
+// Copyright (C) 2010, 2011, 2012 Zeno Gantner
 //
 // This file is part of MyMediaLite.
 //
@@ -26,9 +26,9 @@ public interface IIterativeModel
 		/// <summary>Run one iteration (= pass over the training data)</summary>
 		void Iterate();
 
-		/// <summary>Compute the current loss of the model</summary>
-		/// <returns>the current loss; -1 if not implemented</returns>
-		float ComputeLoss();
+		/// <summary>Compute the current optimization objective (usually loss plus regularization term) of the model</summary>
+		/// <returns>the current objective; -1 if not implemented</returns>
+		float ComputeObjective();
 	}
 }
 
diff --git a/src/MyMediaLite/ItemRecommendation/BPRLinear.cs b/src/MyMediaLite/ItemRecommendation/BPRLinear.cs
@@ -254,7 +254,7 @@ public override void LoadModel(string filename)
 		}
 
 		///
-		public float ComputeLoss()
+		public float ComputeObjective()
 		{
 			return -1;
 		}

diff --git a/src/MyMediaLite/ItemRecommendation/BPRMF.cs b/src/MyMediaLite/ItemRecommendation/BPRMF.cs
@@ -171,7 +171,7 @@ public override void Train()
 					loss_sample_j[c] = j;
 				}
 
-				last_loss = ComputeLoss();
+				last_loss = ComputeObjective();
 			}
 
 			for (int i = 0; i < NumIter; i++)
@@ -250,7 +250,7 @@ public override void Iterate()
 
 			if (BoldDriver)
 			{
-				double loss = ComputeLoss();
+				double loss = ComputeObjective();
 
 				if (loss > last_loss)
 					LearnRate *= 0.5f;
@@ -534,7 +534,7 @@ protected virtual void RetrainItem(int item_id)
 		}
 
 		///
-		public override float ComputeLoss()
+		public override float ComputeObjective()
 		{
 			double ranking_loss = 0;
 			for (int c = 0; c < loss_sample_u.Length; c++)

diff --git a/src/MyMediaLite/ItemRecommendation/MF.cs b/src/MyMediaLite/ItemRecommendation/MF.cs
@@ -77,7 +77,7 @@ public override void Train()
 		public abstract void Iterate();
 
 		///
-		public abstract float ComputeLoss();
+		public abstract float ComputeObjective();
 
 		/// <summary>Predict the weight for a given user-item combination</summary>
 		/// <remarks>

diff --git a/src/MyMediaLite/ItemRecommendation/MultiCoreBPRMF.cs b/src/MyMediaLite/ItemRecommendation/MultiCoreBPRMF.cs
@@ -96,7 +96,7 @@ public override void Iterate()
 
 			if (BoldDriver)
 			{
-				double loss = ComputeLoss();
+				double loss = ComputeObjective();
 
 				if (loss > last_loss)
 					LearnRate *= 0.5f;

diff --git a/src/MyMediaLite/ItemRecommendation/SoftMarginRankingMF.cs b/src/MyMediaLite/ItemRecommendation/SoftMarginRankingMF.cs
@@ -111,7 +111,7 @@ protected override void UpdateFactors(int u, int i, int j, bool update_u, bool u
 
 		/// <summary>Compute approximate loss</summary>
 		/// <returns>the approximate loss</returns>
-		public override float ComputeLoss()
+		public override float ComputeObjective()
 		{
 			throw new NotImplementedException();
 		}

diff --git a/src/MyMediaLite/ItemRecommendation/WRMF.cs b/src/MyMediaLite/ItemRecommendation/WRMF.cs
@@ -143,7 +143,7 @@ protected virtual void Optimize(IBooleanMatrix data, Matrix<float> W, Matrix<flo
 		}
 
 		///
-		public override float ComputeLoss()
+		public override float ComputeObjective()
 		{
 			return -1;
 		}

diff --git a/src/MyMediaLite/RatingPrediction/BiasedMatrixFactorization.cs b/src/MyMediaLite/RatingPrediction/BiasedMatrixFactorization.cs
@@ -160,7 +160,7 @@ protected override void InitModel()
 				item_bias[i] = 0;
 
 			if (BoldDriver)
-				last_loss = ComputeLoss();
+				last_loss = ComputeObjective();
 		}
 
 		///
@@ -212,7 +212,7 @@ public override void Iterate()
 
 			if (BoldDriver)
 			{
-				double loss = ComputeLoss();
+				double loss = ComputeObjective();
 
 				if (loss > last_loss)
 					LearnRate *= 0.5f;
@@ -435,7 +435,7 @@ protected override IList<float> FoldIn(IList<Pair<int, float>> rated_items)
 		}
 
 		///
-		public override float ComputeLoss()
+		public override float ComputeObjective()
 		{
 			double loss = 0;
 			switch (Loss)

diff --git a/src/MyMediaLite/RatingPrediction/CoClustering.cs b/src/MyMediaLite/RatingPrediction/CoClustering.cs
@@ -357,7 +357,7 @@ public override void LoadModel(string filename)
 		}
 
 		///
-		public float ComputeLoss()
+		public float ComputeObjective()
 		{
 			return this.Evaluate(ratings)["RMSE"];
 		}

diff --git a/src/MyMediaLite/RatingPrediction/FactorWiseMatrixFactorization.cs b/src/MyMediaLite/RatingPrediction/FactorWiseMatrixFactorization.cs
@@ -267,7 +267,7 @@ public override void LoadModel(string filename)
 		}
 
 		///
-		public float ComputeLoss()
+		public float ComputeObjective()
 		{
 			return -1;
 		}

diff --git a/src/MyMediaLite/RatingPrediction/LatentFeatureLogLinearModel.cs b/src/MyMediaLite/RatingPrediction/LatentFeatureLogLinearModel.cs
@@ -98,7 +98,7 @@ protected override void Iterate(IList<int> rating_indices, bool update_user, boo
 		}
 
 		///
-		public override float ComputeLoss()
+		public override float ComputeObjective()
 		{
 			double rating_range_size = MaxRating - MinRating;
 

diff --git a/src/MyMediaLite/RatingPrediction/MatrixFactorization.cs b/src/MyMediaLite/RatingPrediction/MatrixFactorization.cs
@@ -374,7 +374,7 @@ public override void LoadModel(string filename)
 
 		/// <summary>Compute the regularized loss</summary>
 		/// <returns>the regularized loss</returns>
-		public virtual float ComputeLoss()
+		public virtual float ComputeObjective()
 		{
 			double loss = 0;
 			for (int i = 0; i < ratings.Count; i++)

diff --git a/src/MyMediaLite/RatingPrediction/SocialMF.cs b/src/MyMediaLite/RatingPrediction/SocialMF.cs
@@ -221,7 +221,7 @@ private void IterateBatch()
 		}
 
 		///
-		public override float ComputeLoss()
+		public override float ComputeObjective()
 		{
 			double loss = 0;
 

diff --git a/src/MyMediaLite/RatingPrediction/TimeAwareBaseline.cs b/src/MyMediaLite/RatingPrediction/TimeAwareBaseline.cs
@@ -289,7 +289,7 @@ public override float Predict(int user_id, int item_id, DateTime time)
 		}
 
 		///
-		public virtual float ComputeLoss()
+		public virtual float ComputeObjective()
 		{
 			double loss =
 				this.Evaluate(ratings)["RMSE"]

diff --git a/src/MyMediaLite/RatingPrediction/TimeAwareBaselineWithFrequencies.cs b/src/MyMediaLite/RatingPrediction/TimeAwareBaselineWithFrequencies.cs
@@ -150,9 +150,9 @@ public override float Predict(int user_id, int item_id, DateTime time)
 		}
 
 		///
-		public override float ComputeLoss()
+		public override float ComputeObjective()
 		{
-			return (float) (base.ComputeLoss() + RegItemBiasAtFrequency * Math.Pow(item_bias_at_frequency.FrobeniusNorm(), 2));
+			return (float) (base.ComputeObjective() + RegItemBiasAtFrequency * Math.Pow(item_bias_at_frequency.FrobeniusNorm(), 2));
 		}
 
 		///

diff --git a/src/MyMediaLite/RatingPrediction/UserItemBaseline.cs b/src/MyMediaLite/RatingPrediction/UserItemBaseline.cs
@@ -239,7 +239,7 @@ public override void LoadModel(string filename)
 		}
 
 		///
-		public float ComputeLoss()
+		public float ComputeObjective()
 		{
 			return (float) (
 				this.Evaluate(ratings)["RMSE"]

diff --git a/...diaLiteExperimental/RatingPrediction/ConstrainedProbabilisticBiasedMatrixFactorization.cs b/...diaLiteExperimental/RatingPrediction/ConstrainedProbabilisticBiasedMatrixFactorization.cs
@@ -95,7 +95,7 @@ protected override void InitModel()
 			similarity_constraint_matrix = new Matrix<float>(NumFactors, MaxItemID + 1);
 
 			//if (BoldDriver)
-			//	last_loss = ComputeLoss();
+			//	last_loss = ComputeObjective();
 		}
 
 		///
@@ -118,7 +118,7 @@ public override void Iterate()
 			/*
 			if (BoldDriver)
 			{
-				double loss = ComputeLoss();
+				double loss = ComputeObjective();
 
 				if (loss > last_loss)
 					LearnRate *= 0.5;
@@ -227,7 +227,7 @@ public override void RemoveItem(int item_id)
 		}
 
 		///
-		public override float ComputeLoss()
+		public override float ComputeObjective()
 		{
 			// TODO
 			return -1;