Author: srowen
Date: Mon Apr 26 14:49:37 2010
New Revision: 938070
URL: http://svn.apache.org/viewvc?rev=938070&view=rev
Log:
Remove normalization by vector length since it was possibly confusing and not
necessarily desirable in all cases. Simplified version is comparably effective.
Modified:
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarity.java
lucene/mahout/trunk/core/src/test/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarityTest.java
Modified:
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarity.java
URL:
http://svn.apache.org/viewvc/lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarity.java?rev=938070&r1=938069&r2=938070&view=diff
==============================================================================
---
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarity.java
(original)
+++
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarity.java
Mon Apr 26 14:49:37 2010
@@ -54,17 +54,8 @@ public final class EuclideanDistanceSimi
@Override
double computeResult(int n, double sumXY, double sumX2, double sumY2, double
sumXYdiff2) {
- if (n == 0) {
- return Double.NaN;
- }
- double denominator = Math.sqrt(sumX2) + Math.sqrt(sumY2);
- if (denominator == 0.0) {
- return Double.NaN;
- }
- // normalize a bit for magnitude
- sumXYdiff2 /= denominator;
- // divide by n below to not automatically give users with more overlap
more similarity
- return 1.0 / (1.0 + Math.sqrt(sumXYdiff2) / n);
+ // divide denominator by n below to not automatically give users with more
overlap more similarity
+ return n / (1.0 + Math.sqrt(sumXYdiff2));
}
}
\ No newline at end of file
Modified:
lucene/mahout/trunk/core/src/test/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarityTest.java
URL:
http://svn.apache.org/viewvc/lucene/mahout/trunk/core/src/test/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarityTest.java?rev=938070&r1=938069&r2=938070&view=diff
==============================================================================
---
lucene/mahout/trunk/core/src/test/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarityTest.java
(original)
+++
lucene/mahout/trunk/core/src/test/java/org/apache/mahout/cf/taste/impl/similarity/EuclideanDistanceSimilarityTest.java
Mon Apr 26 14:49:37 2010
@@ -55,7 +55,7 @@ public final class EuclideanDistanceSimi
{3.0, 3.0},
});
double correlation = new
EuclideanDistanceSimilarity(dataModel).userSimilarity(1, 2);
- assertTrue(Double.isNaN(correlation));
+ assertEquals(1.0, correlation);
}
public void testNoCorrelation1() throws Exception {
@@ -66,7 +66,7 @@ public final class EuclideanDistanceSimi
{-3.0, 2.0},
});
double correlation = new
EuclideanDistanceSimilarity(dataModel).userSimilarity(1, 2);
- assertCorrelationEquals(0.424465381883345, correlation);
+ assertCorrelationEquals(0.24357264905599915, correlation);
}
public void testNoCorrelation1Weighted() throws Exception {
@@ -77,7 +77,7 @@ public final class EuclideanDistanceSimi
{-3.0, 2.0},
});
double correlation = new EuclideanDistanceSimilarity(dataModel,
Weighting.WEIGHTED).userSimilarity(1, 2);
- assertCorrelationEquals(0.8081551272944483, correlation);
+ assertCorrelationEquals(0.747857549685333, correlation);
}
public void testNoCorrelation2() throws Exception {
@@ -88,7 +88,7 @@ public final class EuclideanDistanceSimi
{null, null, 1.0},
});
double correlation = new
EuclideanDistanceSimilarity(dataModel).userSimilarity(1, 2);
- assertTrue(Double.isNaN(correlation));
+ assertEquals(0.0, correlation);
}
public void testNoCorrelation3() throws Exception {
@@ -99,7 +99,7 @@ public final class EuclideanDistanceSimi
{70.0, 80.0, 90.0},
});
double correlation = new
EuclideanDistanceSimilarity(dataModel).userSimilarity(1, 2);
- assertCorrelationEquals(0.3606507916004517, correlation);
+ assertCorrelationEquals(0.10244407226831752, correlation);
}
public void testSimple() throws Exception {
@@ -110,7 +110,7 @@ public final class EuclideanDistanceSimi
{2.0, 5.0, 6.0},
});
double correlation = new
EuclideanDistanceSimilarity(dataModel).userSimilarity(1, 2);
- assertCorrelationEquals(0.5896248568217328, correlation);
+ assertCorrelationEquals(0.5598164905901122, correlation);
}
public void testSimpleWeighted() throws Exception {
@@ -121,7 +121,7 @@ public final class EuclideanDistanceSimi
{2.0, 5.0, 6.0},
});
double correlation = new EuclideanDistanceSimilarity(dataModel,
Weighting.WEIGHTED).userSimilarity(1, 2);
- assertCorrelationEquals(0.8974062142054332, correlation);
+ assertCorrelationEquals(0.889954122647528, correlation);
}
public void testFullItemCorrelation1() throws Exception {
@@ -145,8 +145,7 @@ public final class EuclideanDistanceSimi
});
double correlation =
new EuclideanDistanceSimilarity(dataModel).itemSimilarity(0, 1);
- // Yeah, undefined in this case
- assertTrue(Double.isNaN(correlation));
+ assertEquals(1.0, correlation);
}
public void testNoItemCorrelation1() throws Exception {
@@ -158,7 +157,7 @@ public final class EuclideanDistanceSimi
});
double correlation =
new EuclideanDistanceSimilarity(dataModel).itemSimilarity(0, 1);
- assertCorrelationEquals(0.424465381883345, correlation);
+ assertCorrelationEquals(0.24357264905599915, correlation);
}
public void testNoItemCorrelation2() throws Exception {
@@ -168,9 +167,8 @@ public final class EuclideanDistanceSimi
{null, 1.0, null},
{null, null, 1.0},
});
- double correlation =
- new EuclideanDistanceSimilarity(dataModel).itemSimilarity(1, 2);
- assertTrue(Double.isNaN(correlation));
+ double correlation = new
EuclideanDistanceSimilarity(dataModel).itemSimilarity(1, 2);
+ assertEquals(0.0, correlation);
}
public void testNoItemCorrelation3() throws Exception {
@@ -183,7 +181,7 @@ public final class EuclideanDistanceSimi
});
double correlation =
new EuclideanDistanceSimilarity(dataModel).itemSimilarity(0, 1);
- assertCorrelationEquals(0.3606507916004517, correlation);
+ assertCorrelationEquals(0.10244407226831752, correlation);
}
public void testSimpleItem() throws Exception {
@@ -196,7 +194,7 @@ public final class EuclideanDistanceSimi
});
double correlation =
new EuclideanDistanceSimilarity(dataModel).itemSimilarity(0, 1);
- assertCorrelationEquals(0.5896248568217328, correlation);
+ assertCorrelationEquals(0.5598164905901122, correlation);
}
public void testSimpleItemWeighted() throws Exception {
@@ -209,7 +207,7 @@ public final class EuclideanDistanceSimi
});
ItemSimilarity itemSimilarity = new EuclideanDistanceSimilarity(dataModel,
Weighting.WEIGHTED);
double correlation = itemSimilarity.itemSimilarity(0, 1);
- assertCorrelationEquals(0.8974062142054332, correlation);
+ assertCorrelationEquals(0.889954122647528, correlation);
}
public void testRefresh() throws TasteException {
