Author: gsingers
Date: Fri Nov 4 14:19:44 2011
New Revision: 1197580
URL: http://svn.apache.org/viewvc?rev=1197580&view=rev
Log:
minor javadoc
Modified:
mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveLogisticRegression.java
Modified:
mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveLogisticRegression.java
URL:
http://svn.apache.org/viewvc/mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveLogisticRegression.java?rev=1197580&r1=1197579&r2=1197580&view=diff
==============================================================================
---
mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveLogisticRegression.java
(original)
+++
mahout/trunk/core/src/main/java/org/apache/mahout/classifier/sgd/AdaptiveLogisticRegression.java
Fri Nov 4 14:19:44 2011
@@ -20,9 +20,9 @@ package org.apache.mahout.classifier.sgd
import com.google.common.collect.Lists;
import org.apache.hadoop.io.Writable;
import org.apache.mahout.classifier.OnlineLearner;
-import org.apache.mahout.ep.Payload;
import org.apache.mahout.ep.EvolutionaryProcess;
import org.apache.mahout.ep.Mapping;
+import org.apache.mahout.ep.Payload;
import org.apache.mahout.ep.State;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
@@ -36,7 +36,7 @@ import java.util.Locale;
import java.util.concurrent.ExecutionException;
/**
- * This is a meta-learner that maintains a pool of ordinary
OnlineLogisticRegression learners. Each
+ * This is a meta-learner that maintains a pool of ordinary {@link
org.apache.mahout.classifier.sgd.OnlineLogisticRegression} learners. Each
* member of the pool has different learning rates. Whichever of the learners
in the pool falls
* behind in terms of average log-likelihood will be tossed out and replaced
with variants of the
* survivors. This will let us automatically derive an annealing schedule
that optimizes learning
@@ -45,7 +45,7 @@ import java.util.concurrent.ExecutionExc
* learn also decreases the number of learning rate parameters required and
replaces the normal
* hyper-parameter search.
* <p/>
- * One wrinkle is that the pool of learners that we maintain is actually a
pool of CrossFoldLearners
+ * One wrinkle is that the pool of learners that we maintain is actually a
pool of {@link org.apache.mahout.classifier.sgd.CrossFoldLearner}
* 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
@@ -113,6 +113,7 @@ public class AdaptiveLogisticRegression
record++;
buffer.add(new TrainingExample(trackingKey, groupKey, actual, instance));
+ //don't train until we have enough examples
if (buffer.size() > bufferSize) {
trainWithBufferedExamples();
}
