Java Instances.get方法代碼示例

import weka.core.Instances; //導入方法依賴的package包/類
public static DMatrix instancesToDMatrix(Instances instances) throws XGBoostError {
    long[] rowHeaders = new long[instances.size()+1];
    rowHeaders[0]=0;
    List<Float> dataList = new ArrayList<>();
    List<Integer> colList = new ArrayList<>();
    float[] labels = new float[instances.size()];

    for(int i=0; i<instances.size(); i++) {
        Instance instance = instances.get(i);
        rowHeaders[i] = dataList.size();
        processInstance(instance, dataList, colList);
        labels[i] = (float) instance.classValue();
    }
    rowHeaders[rowHeaders.length - 1] = dataList.size();
    int colNum = instances.numAttributes()-1;
    DMatrix dMatrix = createDMatrix(rowHeaders, dataList, colList, colNum);

    dMatrix.setLabel(labels);
    return dMatrix;

}
 

import weka.core.Instances; //導入方法依賴的package包/類
public static DMatrix instancesToDenseDMatrix(Instances instances) throws XGBoostError {
    int colNum = instances.numAttributes()-1;
    int rowNum = instances.size();

    float[] data = new float[colNum*rowNum];
    float[] labels = new float[instances.size()];
    Attribute classAttribute = instances.classAttribute();
    int classAttrIndex = classAttribute.index();

    for(int i=0, dataIndex = 0; i<instances.size(); i++) {
        Instance instance = instances.get(i);

        labels[i] = (float) instance.classValue();
        Enumeration<Attribute> attributeEnumeration = instance.enumerateAttributes();
        while (attributeEnumeration.hasMoreElements()) {
            Attribute attribute = attributeEnumeration.nextElement();
            int attrIndex = attribute.index();
            if(attrIndex == classAttrIndex){
                continue;
            }
            data[dataIndex]= (float) instance.value(attribute);
            dataIndex++;
        }
    }


    DMatrix dMatrix = new DMatrix(data, rowNum, colNum);

    dMatrix.setLabel(labels);
    return dMatrix;

}
 

import weka.core.Instances; //導入方法依賴的package包/類
public static Instance findBestPerf(Instances data){
	int idx = data.numAttributes()-1;
	double bestPerf = data.attributeStats(idx).numericStats.max;
	for(int i=0;i<data.numInstances();i++)
		if(data.get(i).value(idx)==bestPerf)
			return data.get(i);
	return null;//should never return NULL
}
 

import weka.core.Instances; //導入方法依賴的package包/類
@Override
public Instances collectPerfs(Instances samplePoints, String perfAttName) {
	Instances retVal = null;
	
	if(samplePoints.attribute(perfAttName) == null){
		Attribute performance = new Attribute(perfAttName);
		samplePoints.insertAttributeAt(performance, samplePoints.numAttributes());
	}
	
	File perfFolder = new File(perfsfilepath);
	int tot=0;
	if(perfFolder.exists()){
		//let's get all the name set for the sample points
		Iterator<Instance> itr = samplePoints.iterator();
		TreeSet<String> insNameSet = new TreeSet<String>();
		HashMap<String, Integer> mapping = new HashMap<String, Integer>();
		int pos=0;
		while(itr.hasNext()){
			String mdstr = getMD5(itr.next());
			insNameSet.add(mdstr);
			mapping.put(mdstr, new Integer(pos++));
		}
		
		//now we collect
		File[] perfFiles = perfFolder.listFiles(new PerfsFileFilter(insNameSet));
		tot = perfFiles.length;
		if(tot > 0) isInterrupt = true;
		for(int i=0;i<tot;i++){
			Instance ins = samplePoints.get(mapping.get(perfFiles[i].getName()));
			double[] results = getPerf(perfFiles[i].getAbsolutePath());
			if(results!=null){
				ins.setValue(samplePoints.numAttributes()-1, results[0]);
			}
		}
	}
	retVal = samplePoints;
	retVal.setClassIndex(retVal.numAttributes()-1);
	System.out.println("Total number of collected performances is : "+tot);
	return retVal;
}
 

import weka.core.Instances; //導入方法依賴的package包/類
/**
 * Calculate Weighted Relative Accuracy (WRA) for from the input dataset for a given rule.
 * 
 * @param dataset the dataset
 * @param aLeftHandSide left-side (BODY) of the rule
 * @param aRightHandSide right-side (HEAD) of the rule
 * @return WRA value of the rule on the dataset
 */
public double calcualteWRA(Instances dataset, List<Term> aLeftHandSide, List<Term> aRightHandSide){
    
    double totalPositive;
    double totalNegative;
    
    double ruleTruePositive = 0;
    double ruleFalsePositive = 0;
    
    double ruleTrueNegative = 0;
    double ruleFalseNegative = 0;
    
    
    // calcualte truePositive, trueNegative, falsePostive, falseNegative for the Rules
    for (int instanceI = 0; instanceI < dataset.size(); instanceI++) {
        
        Instance anInstance = dataset.get(instanceI);
        
        // calculate true postive and true negative instances for the rules
        if(instanceCoveredByTermsList(anInstance, aLeftHandSide)){
            
            if(instanceCoveredByTermsList(anInstance, aRightHandSide)){
                ruleTruePositive++;
            }else{
                ruleFalsePositive++;
            }
        }else if(instanceCoveredByTermsList(anInstance, aRightHandSide)){
            ruleFalsePositive++;
        }else{
            ruleTrueNegative++;
        }
    }
    
    // calculate totalPositive and totalNegative
    totalPositive = ruleTruePositive + ruleFalseNegative;
    totalNegative = ruleFalsePositive + ruleTrueNegative;
    
    // start calcualting WRA      
    double ruleWRA = (ruleTruePositive + ruleFalsePositive) / (totalPositive + totalNegative) * 
            (  (ruleTruePositive / (ruleTruePositive + ruleFalsePositive) - ( totalPositive / (totalPositive + totalNegative) )));
    
    return ruleWRA; 
}
 

import weka.core.Instances; //導入方法依賴的package包/類
public Instances runExp(Instances samplePoints, String perfAttName){
	Instances retVal = null;
	if(samplePoints.attribute(perfAttName) == null){
		Attribute performance = new Attribute(perfAttName);
		samplePoints.insertAttributeAt(performance, samplePoints.numAttributes());
	}
	int pos = samplePoints.numInstances();
	int count = 0;
	for (int i = 0; i < pos; i++) {
		Instance ins = samplePoints.get(i);
		HashMap hm = new HashMap();
		int tot = 0;
		for (int j = 0; j < ins.numAttributes(); j++) {
			hm.put(ins.attribute(j).name(), ins.value(ins.attribute(j)));
		}

		boolean testRet;
		if (Double.isNaN(ins.value(ins.attribute(ins.numAttributes() - 1)))) {
			testRet = this.startTest(hm, i, isInterrupt);
			double y = 0;
			if (!testRet) {// the setting does not work, we skip it
				y = -1;
				count++;
				if (count >= targetTestErrorNum) {
					System.out.println("There must be somthing wrong with the system. Please check and restart.....");
					System.exit(1);
				}
			} else {
				y = getPerformanceByType(performanceType);
				count = 0;
			}

			ins.setValue(samplePoints.numAttributes() - 1, y);
			writePerfstoFile(ins);
		} else {
			continue;
		}
	}
	retVal = samplePoints;
	retVal.setClassIndex(retVal.numAttributes()-1);
	
	return retVal;
}