/**
* KMeans constructor: the cluster centroids are obtained for the given dataset. Firstly, the
* cluster's centroids are randomly chosen. Then the centroids are updated as the mean vlaue of
* nearest examples in the dataset. The updating is carried out until no changes in the centroids
* is achieved.
*
* @param X The dataset to be clusterized
* @param nclusters The desired number of clusters
* @param vrand The Randomize object to be used
*/
public KMeans(double[][] X, int nclusters, Randomize vrand) {
rand = vrand;
train = X;
clusters = nclusters;
cclusters = new double[nclusters][X[0].length];
for (int i = 0; i < nclusters; i++) {
int pos = (int) (rand.Rand() * X.length);
for (int j = 0; j < cclusters[i].length; j++) cclusters[i][j] = X[pos][j];
}
int[] C = new int[X.length];
int[] C_old = new int[X.length];
for (int i = 0; i < X.length; i++) {
C_old[i] = nearestCentroid(X[i]);
}
centroidsUpdating(C_old);
int cambios = 0, iteracion = 0;
do {
iteracion++;
System.out.println("Iter=" + iteracion + " changes=" + cambios);
cambios = 0;
for (int i = 0; i < X.length; i++) {
C[i] = nearestCentroid(X[i]);
if (C[i] != C_old[i]) cambios++;
C_old[i] = C[i];
}
centroidsUpdating(C);
} while (cambios > 0);
}
/**
* This public static method runs the algorithm that this class concerns with.
*
* @param args Array of strings to sent parameters to the main program. The path of the
* algorithm's parameters file must be given.
*/
public static void main(String args[]) {
boolean tty = false;
ProcessConfig pc = new ProcessConfig();
System.out.println("Reading configuration file: " + args[0]);
if (pc.fileProcess(args[0]) < 0) return;
int algo = pc.parAlgorithmType;
rand = new Randomize();
rand.setSeed(pc.parSeed);
ModelFuzzyPittsBurgh pi = new ModelFuzzyPittsBurgh();
pi.fuzzyPittsburghModelling(tty, pc);
}
/**
* This public static method runs the algorithm that this class concerns with.
*
* @param args Array of strings to sent parameters to the main program. The path of the
* algorithm's parameters file must be given.
*/
public static void main(String args[]) {
boolean tty = false;
ProcessConfig pc = new ProcessConfig();
System.out.println("Reading configuration file: " + args[0]);
if (pc.fileProcess(args[0]) < 0) return;
int algo = pc.parAlgorithmType;
rand = new Randomize();
rand.setSeed(pc.parSeed);
ClusterKMeans km = new ClusterKMeans();
km.clustering_kmeans(tty, pc);
}
/**
* This method reads a configuration file and calls statisticalTest with appropriate values to run
* the Mann Whitney U test for classification problems, defined in StatTest class
*
* @param args A string that contains the command line arguments
*/
public static void main(String args[]) {
boolean tty = false;
ProcessConfig pc = new ProcessConfig();
System.out.println("Reading configuration file: " + args[0]);
if (pc.fileProcess(args[0]) < 0) return;
int algorithm = pc.parAlgorithmType;
rand = new Randomize();
rand.setSeed(pc.parSeed);
ParseFileList pl = new ParseFileList();
pl.statisticalTest(StatTest.MannWhitneyC, tty, pc);
}