svn commit: r986798 - /mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveAnnealedLogisticRegression.java

[td...@apache.org]

Author: tdunning
Date: Wed Aug 18 17:26:38 2010
New Revision: 986798

URL: http://svn.apache.org/viewvc?rev=986798&view=rev
Log:
Added comment.

Modified:
    mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveAnnealedLogisticRegression.java

Modified: mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveAnnealedLogisticRegression.java
URL: http://svn.apache.org/viewvc/mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveAnnealedLogisticRegression.java?rev=986798&r1=986797&r2=986798&view=diff
==============================================================================
--- mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveAnnealedLogisticRegression.java (original)
+++ mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveAnnealedLogisticRegression.java Wed Aug 18 17:26:38 2010
@@ -18,6 +18,13 @@ import java.util.List;
  * seem that it would to maintain multiple learners in memory.  Doing this adaptation on-line as we
  * learn also decreases the number of learning rate parameters required and replaces the normal
  * hyper-parameter search.
+ *
+ * One wrinkle is that the pool of learners that we maintain is actually a pool of CrossFoldLearners
+ * which themselves contain several OnlineLogisticRegression objects.  These pools allow estimation
+ * of performance on the fly even if we make many passes through the data.  This does, however, increase
+ * the cost of training since if we are using 5-fold cross-validation, each vector is used 4 times for
+ * training and once for classification.  If this becomes a problem, then we should probably use a
+ * 2-way unbalanced train/test split rather than full cross validation.
  */
 public class AdaptiveAnnealedLogisticRegression   implements OnlineLearner {
   private int record = 0;