/**
* Main method for ABB, that explores the search space by pruning nodes and checking their
* inconsistency ratio.
*/
private void runABB() {
boolean[] root = startSolution();
System.arraycopy(root, 0, features, 0, root.length);
abb(root);
/* checks if a subset satisfies the condition (more than 0 selected features) */
if (features == null) {
System.err.println("ERROR: It couldn't be possible to find any solution.");
System.exit(0);
}
}
/**
* Constructor of the Class Parametros
*
* @param nombreFileParametros is the pathname of input parameter file
*/
Parametros(String nombreFileParametros) {
try {
int i;
String fichero, linea, tok;
StringTokenizer lineasFile, tokens;
/* read the parameter file using Files class */
fichero = Files.readFile(nombreFileParametros);
fichero += "\n";
/* remove all \r characters. it is neccesary for a correst use in Windows and UNIX */
fichero = fichero.replace('\r', ' ');
/* extracts the differents tokens of the file */
lineasFile = new StringTokenizer(fichero, "\n");
i = 0;
while (lineasFile.hasMoreTokens()) {
linea = lineasFile.nextToken();
i++;
tokens = new StringTokenizer(linea, " ,\t");
if (tokens.hasMoreTokens()) {
tok = tokens.nextToken();
if (tok.equalsIgnoreCase("algorithm")) nameAlgorithm = getParamString(tokens);
else if (tok.equalsIgnoreCase("inputdata")) getInputFiles(tokens);
else if (tok.equalsIgnoreCase("outputdata")) getOutputFiles(tokens);
else if (tok.equalsIgnoreCase("seed")) seed = getParamLong(tokens);
else throw new java.io.IOException("Syntax error on line " + i + ": [" + tok + "]\n");
}
}
} catch (java.io.FileNotFoundException e) {
System.err.println(e + "Parameter file");
} catch (java.io.IOException e) {
System.err.println(e + "Aborting program");
System.exit(-1);
}
/** show the read parameter in the standard output */
String contents = "-- Parameters echo --- \n";
contents += "Algorithm name: " + nameAlgorithm + "\n";
contents += "Input Train File: " + trainFileNameInput + "\n";
contents += "Input Test File: " + testFileNameInput + "\n";
contents += "Output Train File: " + trainFileNameOutput + "\n";
contents += "Output Test File: " + testFileNameOutput + "\n";
System.out.println(contents);
}
/**
* Removes one feature at a time, starting from the furthest on the right
*
* @param featuresVector solution to generate its neighbor
* @param which number of the feature to remove starting from the right
* @return next neighbor of the given solution with one less feature
*/
private static boolean[] removeOne(boolean featuresVector[], int which) {
boolean[] fv = new boolean[featuresVector.length];
System.arraycopy(featuresVector, 0, fv, 0, fv.length);
boolean stop = false;
int count = 0;
for (int i = fv.length - 1; i >= 0 && !stop; i--) {
if (fv[i]) {
count++;
if (count == which) {
fv[i] = false;
stop = true;
}
}
}
return fv;
}
/** Recursive method for ABB */
private void abb(boolean feat[]) {
boolean[] child;
double measure;
threshold = data.measureIEP(feat);
for (int i = 0; i < cardinalidadCto(feat); i++) {
child = removeOne(feat, i);
measure = data.measureIEP(child);
if (legitimate(child) && measure < threshold) {
if (measure < data.measureIEP(features)) {
// we keep the best found in 'features'
System.arraycopy(child, 0, features, 0, child.length);
}
abb(child);
} else { // we prune this node
pruned.add(child);
}
}
}
