protected Vector discretizeAttribute(int attribute, int[] values, int begin, int end) {
Vector cd = classDistribution(attribute, values, begin, end);
if (cd.size() == 1) return new Vector();
int numValues = sumValues(cd);
double entAll = computeEntropy(cd, numValues);
Vector candidateCutPoints = getCandidateCutPoints(attribute, values, begin, end);
if (candidateCutPoints.size() == 0) return new Vector();
int posMin = ((Integer) candidateCutPoints.elementAt(0)).intValue();
double entMin = computePartitionEntropy(attribute, values, begin, posMin, end);
for (int i = 1, size = candidateCutPoints.size(); i < size; i++) {
int pos = ((Integer) candidateCutPoints.elementAt(i)).intValue();
double ent = computePartitionEntropy(attribute, values, begin, pos, end);
if (ent < entMin) {
entMin = ent;
posMin = pos;
}
}
if (entMin < entAll) {
Vector res1 = discretizeAttribute(attribute, values, begin, posMin - 1);
double cutPoint =
(realValues[attribute][values[posMin - 1]] + realValues[attribute][values[posMin]]) / 2.0;
res1.addElement(new Double(cutPoint));
Vector res2 = discretizeAttribute(attribute, values, posMin, end);
res1.addAll(res2);
return res1;
}
return new Vector();
}
int sumValues(Vector v) {
int sum = 0;
for (int i = 0, size = v.size(); i < size; i++) {
sum += ((Integer) v.elementAt(i)).intValue();
}
return sum;
}
double computeEntropy(Vector v, int numValues) {
double ent = 0;
for (int i = 0, size = v.size(); i < size; i++) {
double prob = ((Integer) v.elementAt(i)).intValue();
prob /= (double) numValues;
ent += prob * Math.log(prob) / Math.log(2);
}
return -ent;
}
