Java 类org.apache.commons.math3.linear.SparseRealVector 实例源码

public void getTopK(int testIndex, int numPred, ArrayList<String> predictions, ArrayList<Double> confidenceScores)
{
 int size = docs[0].vector.getDimension();
 SparseRealVector onesVector = new OpenMapRealVector(size);
 for(int i=0; i<size; i++)
 {
     onesVector.setEntry(i, 1); 
 }

 List<Prediction> sortedPredictions = new ArrayList<Prediction>();  // descending order of jaccard similarity

 for(int i=0; i<info.noTrainingDocs; i++)
 {
     double jacSim = getJaccardSimilarity(docs[i], docs[info.noTrainingDocs + testIndex], onesVector);
     Prediction pred = new Prediction(new Integer(i).toString(), jacSim);
     if(jacSim > 0.0)
     {
         sortedPredictions.add(pred);
     }
     //System.out.println(i+" "+jacSim);
 }

 Collections.sort(sortedPredictions, new PredictionComparator());

 //System.out.println("no of predictions = "+sortedPredictions.size());

    for(int j=0; j<numPred && j<sortedPredictions.size(); j++)
    {
        predictions.add(sortedPredictions.get(j).predictionIndex);
        confidenceScores.add(sortedPredictions.get(j).confidenceScore);
    }   

}

public static double getJaccardSimilarity(DocVector d1, DocVector d2, SparseRealVector onesVector) {
 return (d1.vector.dotProduct(d2.vector)) / (d1.vector.dotProduct(onesVector) + d2.vector.dotProduct(onesVector) - d1.vector.dotProduct(d2.vector)); 
}