Index: trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaBaggingTraining.java
===================================================================
--- trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaBaggingTraining.java	(revision 24)
+++ trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaBaggingTraining.java	(revision 25)
@@ -23,4 +23,5 @@
  * 
  * all subsequent parameters are configuration params (for example for trees)
+ * Cross Validation params always come last and are prepended with -CVPARAM
  * 
  * XML Configurations for Weka Classifiers:
@@ -28,6 +29,6 @@
  * {@code
  * <!-- examples -->
- * <setwisetrainer name="WekaBaggingTraining2" param="NaiveBayesBagging weka.classifiers.bayes.NaiveBayes" />
- * <setwisetrainer name="WekaBaggingTraining2" param="LogisticBagging weka.classifiers.functions.Logistic -R 1.0E-8 -M -1" />
+ * <setwisetrainer name="WekaBaggingTraining" param="NaiveBayesBagging weka.classifiers.bayes.NaiveBayes" />
+ * <setwisetrainer name="WekaBaggingTraining" param="LogisticBagging weka.classifiers.functions.Logistic -R 1.0E-8 -M -1" />
  * }
  * </pre>
Index: trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaBaseTraining.java
===================================================================
--- trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaBaseTraining.java	(revision 24)
+++ trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaBaseTraining.java	(revision 25)
@@ -16,6 +16,6 @@
  * 
  * Important conventions of the XML format: 
- * Cross Validation params come always last and are prepended with -CVPARAM
- * Example: <trainer name="WekaClusterTraining2" param="RandomForestLocal weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5"/>
+ * Cross Validation params always come last and are prepended with -CVPARAM
+ * Example: <trainer name="WekaTraining" param="RandomForestLocal weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5"/>
  */
 public abstract class WekaBaseTraining implements IWekaCompatibleTrainer {
Index: trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalEMTraining.java
===================================================================
--- trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalEMTraining.java	(revision 24)
+++ trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalEMTraining.java	(revision 25)
@@ -22,6 +22,7 @@
 
 /**
- * WekaClusterTraining2
- * 
+ * WekaLocalEMTraining
+ * 
+ * Local Trainer with EM Clustering for data partitioning.
  * Currently supports only EM Clustering.
  * 
@@ -35,5 +36,5 @@
  * 
  * <!-- cluster trainer -->
- * <trainer name="WekaClusterTraining2" param="NaiveBayes weka.classifiers.bayes.NaiveBayes" />
+ * <trainer name="WekaLocalEMTraining" param="NaiveBayes weka.classifiers.bayes.NaiveBayes" />
  */
 public class WekaLocalEMTraining extends WekaBaseTraining implements ITrainingStrategy {
Index: trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalFQTraining.java
===================================================================
--- trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalFQTraining.java	(revision 24)
+++ trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalFQTraining.java	(revision 25)
@@ -30,5 +30,5 @@
  * IEEE Transactions on Software Engineering, vol. 39, no. 6, pp. 822-834, June, 2013  
  * 
- * With WekaLocalTraining2 we do the following:
+ * With WekaLocalFQTraining we do the following:
  * 1) Run the Fastmap algorithm on all training data, let it calculate the 2 most significant 
  *    dimensions and projections of each instance to these dimensions
Index: trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaTraining.java
===================================================================
--- trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaTraining.java	(revision 24)
+++ trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaTraining.java	(revision 25)
@@ -16,4 +16,5 @@
  * 
  * all subsequent parameters are configuration params (for example for trees)
+ * Cross Validation params always come last and are prepended with -CVPARAM
  * 
  * XML Configurations for Weka Classifiers:
@@ -21,6 +22,6 @@
  * {@code
  * <!-- examples -->
- * <trainer name="WekaTraining2" param="NaiveBayes weka.classifiers.bayes.NaiveBayes" />
- * <trainer name="WekaTraining2" param="Logistic weka.classifiers.functions.Logistic -R 1.0E-8 -M -1" />
+ * <trainer name="WekaTraining" param="NaiveBayes weka.classifiers.bayes.NaiveBayes" />
+ * <trainer name="WekaTraining" param="Logistic weka.classifiers.functions.Logistic -R 1.0E-8 -M -1" />
  * }
  * </pre>