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ClusterAnalysis.java
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ClusterAnalysis.java
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public class ClusterAnalysis {
public ClusterAnalysis() {
}
public double clusterVariance(int[][] cluster, int[] centroids) {
double part_first = (1.0 / ((double) cluster.length - 1.0));
double[] sum = { 0.0, 0.0 };
for (int i = 0; i < cluster.length; i++) {
for (int j = 0; j < centroids.length; j++) {
sum[j] += (cluster[i][j] - centroids[j]);
}
}
double jumlah = (sum[0] * sum[0]) + (sum[1] * sum[1]);
// System.out.println(jumlah);
double result = part_first * jumlah;
// System.out.println(part_first);
return result;
}
public double varianceWithinCluster(double[] clusterVariance, int n, int[] nI) {
int k = clusterVariance.length;
double part_first = 1.0 / ((double) n - k);
double sum = 0.0;
for (int i = 0; i < k; i++) {
sum += ((double) nI[i] - 1) * clusterVariance[i];
}
double result = part_first * sum;
return result;
}
public double varianceBetweenClusters(int[] nI, int[][] centroids, double[] centroid) {
int k = nI.length;
double part_first = 1.0 / (((double) k) - 1.0);
double temp = 0.0;
for (int i = 0; i < centroids.length; i++) {
double[] sum = { 0.0, 0.0 };
for (int j = 0; j < centroids[0].length; j++) {
sum[j] += (((double) centroids[i][j]) - centroid[j]);
}
double result = 0.0;
for (int l = 0; l < centroids[0].length; l++) {
result += sum[l] * sum[l];
}
temp += ((double) nI[i]) * result;
}
double last = part_first * temp;
return last;
}
public double varianceAll(double vw, double vb) {
return (vw / vb);
}
}