private SpectralClustering cluster(double[][] data, int k) {
long clock = System.currentTimeMillis();
SpectralClustering cluster = new SpectralClustering(data, k, 0.27);
System.out.format(
"DBSCAN clusterings %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
System.out.println("getNumClusters:" + cluster.getNumClusters());
System.out.println("getClusterSize:" + cluster.getClusterSize());
// System.out.println(JSON.toJSONString(dbscan.getClusterSize()));
System.out.println("toString:" + cluster.toString());
return cluster;
}
private void _cluster(double[][] data, int k) {
long clock = System.currentTimeMillis();
SpectralClustering cluster = new SpectralClustering(data, k, 0.355);
System.out.format(
"DBSCAN clusterings %d samples in %dms\n", data.length, System.currentTimeMillis() - clock);
System.out.println("getNumClusters:" + cluster.getNumClusters());
System.out.println("getClusterSize:" + cluster.getClusterSize());
// System.out.println(JSON.toJSONString(dbscan.getClusterSize()));
System.out.println("toString:" + cluster.toString());
/** ************************************************************ */
boolean more = true;
EigenValueDecomposition eigen = cluster.getEigen();
double[] lab = eigen.getEigenValues();
double sd = smile.math.Math.sd(eigen.getEigenValues());
System.out.println("sd(eigen.getEigenValues()):" + sd);
if (Math.min(eigen.getEigenValues()) > 0.3) {
result = cluster;
cluster(data, k + 1);
} else {
return;
}
}
