Ignore:
Timestamp:
11/05/14 17:40:10 (10 years ago)
Author:
atrautsch
Message:

comment fixes

Location:
trunk/CrossPare/src/de/ugoe/cs/cpdp/training
Files:
5 edited

Legend:

Unmodified
Added
Removed

  • trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaBaggingTraining.java

    r23 r25  
    2323 *  
    2424 * all subsequent parameters are configuration params (for example for trees) 
     25 * Cross Validation params always come last and are prepended with -CVPARAM 
    2526 *  
    2627 * XML Configurations for Weka Classifiers: 
    … …  
    2829 * {@code 
    2930 * <!-- examples --> 
    30  * <setwisetrainer name="WekaBaggingTraining2" param="NaiveBayesBagging weka.classifiers.bayes.NaiveBayes" /> 
    31  * <setwisetrainer name="WekaBaggingTraining2" param="LogisticBagging weka.classifiers.functions.Logistic -R 1.0E-8 -M -1" /> 
     31 * <setwisetrainer name="WekaBaggingTraining" param="NaiveBayesBagging weka.classifiers.bayes.NaiveBayes" /> 
     32 * <setwisetrainer name="WekaBaggingTraining" param="LogisticBagging weka.classifiers.functions.Logistic -R 1.0E-8 -M -1" /> 
    3233 * } 
    3334 * </pre> 

  • trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaBaseTraining.java

    r24 r25  
    1616 *  
    1717 * Important conventions of the XML format:  
    18  * Cross Validation params come always last and are prepended with -CVPARAM 
    19  * Example: <trainer name="WekaClusterTraining2" param="RandomForestLocal weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5"/> 
     18 * Cross Validation params always come last and are prepended with -CVPARAM 
     19 * Example: <trainer name="WekaTraining" param="RandomForestLocal weka.classifiers.trees.RandomForest -CVPARAM I 5 25 5"/> 
    2020 */ 
    2121public abstract class WekaBaseTraining implements IWekaCompatibleTrainer { 

  • trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalEMTraining.java

    r23 r25  
    2222 
    2323/** 
    24  * WekaClusterTraining2 
    25  *  
     24 * WekaLocalEMTraining 
     25 *  
     26 * Local Trainer with EM Clustering for data partitioning. 
    2627 * Currently supports only EM Clustering. 
    2728 *  
    … …  
    3536 *  
    3637 * <!-- cluster trainer --> 
    37  * <trainer name="WekaClusterTraining2" param="NaiveBayes weka.classifiers.bayes.NaiveBayes" /> 
     38 * <trainer name="WekaLocalEMTraining" param="NaiveBayes weka.classifiers.bayes.NaiveBayes" /> 
    3839 */ 
    3940public class WekaLocalEMTraining extends WekaBaseTraining implements ITrainingStrategy { 

  • trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaLocalFQTraining.java

    r23 r25  
    3030 * IEEE Transactions on Software Engineering, vol. 39, no. 6, pp. 822-834, June, 2013   
    3131 *  
    32  * With WekaLocalTraining2 we do the following: 
     32 * With WekaLocalFQTraining we do the following: 
    3333 * 1) Run the Fastmap algorithm on all training data, let it calculate the 2 most significant  
    3434 *    dimensions and projections of each instance to these dimensions 

  • trunk/CrossPare/src/de/ugoe/cs/cpdp/training/WekaTraining.java

    r23 r25  
    1616 *  
    1717 * all subsequent parameters are configuration params (for example for trees) 
     18 * Cross Validation params always come last and are prepended with -CVPARAM 
    1819 *  
    1920 * XML Configurations for Weka Classifiers: 
    … …  
    2122 * {@code 
    2223 * <!-- examples --> 
    23  * <trainer name="WekaTraining2" param="NaiveBayes weka.classifiers.bayes.NaiveBayes" /> 
    24  * <trainer name="WekaTraining2" param="Logistic weka.classifiers.functions.Logistic -R 1.0E-8 -M -1" /> 
     24 * <trainer name="WekaTraining" param="NaiveBayes weka.classifiers.bayes.NaiveBayes" /> 
     25 * <trainer name="WekaTraining" param="Logistic weka.classifiers.functions.Logistic -R 1.0E-8 -M -1" /> 
    2526 * } 
    2627 * </pre> 
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