Ignore:
Timestamp:
08/25/14 12:52:14 (10 years ago)
Author:
sherbold
Message:
  • added some source code comments
Location:
trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing
Files:
3 edited

Legend:

Unmodified
Added
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  • trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing/DataGravitation.java

    r2 r10  
    77import weka.core.Instances; 
    88 
    9 // TODO comment 
     9/** 
     10 * Implements an approach for data weighting suggested after Y. Ma, G. Luo, X. Zeng, and A. Chen: Transfer learning for 
     11 * cross-company software defect prediction. The instances are weighted higher, the more attributes are within the range they are in the training data.  
     12 * @author Steffen Herbold 
     13 */ 
    1014public class DataGravitation implements IProcessesingStrategy, ISetWiseProcessingStrategy { 
    1115 
  • trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing/InformationGainFilter.java

    r2 r10  
    6262         
    6363        /** 
    64          * Internal helper function. TODO 
    65          * @param testdata 
    66          * @param traindata 
    67          * @param removeFromTest 
     64         * Internal helper function for the application of the filter to both all data set as well as a single data set. 
     65         * @param testdata data of the target product 
     66         * @param traindata data of the training product 
     67         * @param removeFromTest defines whether the attributes shall be removed from the test data as well or not 
    6868         */ 
    6969        private void apply(Instances testdata, Instances traindata, boolean removeFromTest) { 
  • trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing/Undersampling.java

    r2 r10  
    77import weka.filters.supervised.instance.Resample; 
    88 
    9 // TODO comment 
     9/** 
     10 * Implements undersampling, a strategy for handling bias in data. In case there are less positive samples (i.e. defect-prone) samples in the 
     11 * data than negative samples (i.e. non-defect-prone), the non-defect-prone entities are sampled such thatthe number of defect-prone and non-defect-prone instances is the same afterwards.   
     12 * @author Steffen Herbold 
     13 */ 
    1014public class Undersampling implements IProcessesingStrategy, 
    1115                ISetWiseProcessingStrategy { 
     
    2125        } 
    2226 
    23  
     27        /* 
     28         * (non-Javadoc) 
     29         * @see de.ugoe.cs.cpdp.dataprocessing.ISetWiseProcessingStrategy#apply(weka.core.Instances, org.apache.commons.collections4.list.SetUniqueList) 
     30         */ 
    2431        @Override 
    2532        public void apply(Instances testdata, SetUniqueList<Instances> traindataSet) { 
     
    2936        } 
    3037 
     38        /* 
     39         * (non-Javadoc) 
     40         * @see de.ugoe.cs.cpdp.dataprocessing.IProcessesingStrategy#apply(weka.core.Instances, weka.core.Instances) 
     41         */ 
    3142        @Override 
    3243        public void apply(Instances testdata, Instances traindata) { 
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