Author: srowen
Date: Fri Jun 5 14:35:19 2009
New Revision: 782031
URL: http://svn.apache.org/viewvc?rev=782031&view=rev
Log:
Fix a misspelling, tiny method change
Modified:
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/eval/GenericRecommenderIRStatsEvaluator.java
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/BooleanUserGenericUserBasedRecommender.java
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/TreeClusteringRecommender.java
Modified:
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/eval/GenericRecommenderIRStatsEvaluator.java
URL:
http://svn.apache.org/viewvc/lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/eval/GenericRecommenderIRStatsEvaluator.java?rev=782031&r1=782030&r2=782031&view=diff
==============================================================================
---
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/eval/GenericRecommenderIRStatsEvaluator.java
(original)
+++
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/eval/GenericRecommenderIRStatsEvaluator.java
Fri Jun 5 14:35:19 2009
@@ -150,10 +150,10 @@
return new IRStatisticsImpl(precision.getAverage(), recall.getAverage(),
fallOut.getAverage());
}
- private void processOtherUser(Object id,
- Collection<Item> relevantItems,
- Collection<User> trainingUsers,
- User user2) {
+ private static void processOtherUser(Object id,
+ Collection<Item> relevantItems,
+ Collection<User> trainingUsers,
+ User user2) {
if (id.equals(user2.getID())) {
List<Preference> trainingPrefs = new ArrayList<Preference>();
Preference[] prefs2 = user2.getPreferencesAsArray();
Modified:
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/BooleanUserGenericUserBasedRecommender.java
URL:
http://svn.apache.org/viewvc/lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/BooleanUserGenericUserBasedRecommender.java?rev=782031&r1=782030&r2=782031&view=diff
==============================================================================
---
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/BooleanUserGenericUserBasedRecommender.java
(original)
+++
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/BooleanUserGenericUserBasedRecommender.java
Fri Jun 5 14:35:19 2009
@@ -175,7 +175,7 @@
* This computation is in a technical sense, wrong, since in the domain of
"boolean preference users"
* where all preference values are 1, this method should only ever return
1.0 or NaN. This isn't
* terribly useful however since it means results can't be ranked by
preference value (all are 1).
- * So instead this returns a sum of similarties to any other user in the
neighborhood who has also
+ * So instead this returns a sum of similarities to any other user in the
neighborhood who has also
* rated the item.
*/
private double doEstimatePreference(User theUser, Collection<User>
theNeighborhood, Object itemID)
Modified:
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/TreeClusteringRecommender.java
URL:
http://svn.apache.org/viewvc/lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/TreeClusteringRecommender.java?rev=782031&r1=782030&r2=782031&view=diff
==============================================================================
---
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/TreeClusteringRecommender.java
(original)
+++
lucene/mahout/trunk/core/src/main/java/org/apache/mahout/cf/taste/impl/recommender/TreeClusteringRecommender.java
Fri Jun 5 14:35:19 2009
@@ -145,7 +145,7 @@
}
/**
- * @param dataModel {...@link DataModel} which provdes {...@link User}s
+ * @param dataModel {...@link DataModel} which provides {...@link User}s
* @param clusterSimilarity {...@link ClusterSimilarity} used to compute
cluster similarity
* @param clusteringThreshold clustering similarity threshold; clusters will
be aggregated into larger
* clusters until the next two nearest clusters' similarity drops below this
threshold
