// KMeans++ re-clustering
private static double[][] recluster(
double[][] points, Random rand, int N, Initialization init, String[][] isCats) {
double[][] res = new double[N][];
res[0] = points[0];
int count = 1;
ClusterDist cd = new ClusterDist();
switch (init) {
case Random:
break;
case PlusPlus:
{ // k-means++
while (count < res.length) {
double sum = 0;
for (double[] point1 : points) sum += minSqr(res, point1, isCats, cd, count);
for (double[] point : points) {
if (minSqr(res, point, isCats, cd, count) >= rand.nextDouble() * sum) {
res[count++] = point;
break;
}
}
}
break;
}
case Furthest:
{ // Takes cluster center further from any already chosen ones
while (count < res.length) {
double max = 0;
int index = 0;
for (int i = 0; i < points.length; i++) {
double sqr = minSqr(res, points[i], isCats, cd, count);
if (sqr > max) {
max = sqr;
index = i;
}
}
res[count++] = points[index];
}
break;
}
default:
throw H2O.fail();
}
return res;
}
