kmeans算法Java实现.doc

(1);classCentroid{   privatedoublemCx,mCy;   privateClustermCluster;   entroid(doublecx,doublecy){       =cx;       =cy;   }   entroid(){//onlycalledbyCAInstance       intnumDP=();       doubletempX=0,tempY=0;       inti;       //caluclatingthenewCentroid       for(i=0;i<numDP;i++){           tempX=tempX+(i).getX();           //totalforx           tempY=tempY+(i).getY();           //totalfory       }       =tempX/numDP;       =tempY/numDP;       //calculatingthenewEuclideanDistanceforeachDataPoint       tempX=0;       tempY=0;       for(i=0;i<numDP;i++){           (i).calcEuclideanDistance();       }       //calculatethenewSumofSquaresfortheCluster       ();   }   publicvoidsetCluster(Clusterc){       =c;   }   publicdoublegetCx(){       returnmCx;   }   publicdoublegetCy(){       returnmCy;   }   lustergetCluster(){       returnmCluster;   }2); classCluster{   privateStringmName;   privateCentroidmCentroid;   privatedoublemSumSqr;   privateVectormDataPoints;   luster(Stringname){       =name;       =null;//willbesetbycallingsetCentroid()       mDataPoints=newVector();   }   publicvoidsetCentroid(Centroidc){       mCentroid=c;   }   entroidgetCentroid(){