/**
* Prints label for subset index of instances (eg class).
*
* @exception Exception if something goes wrong
*/
public final String dumpLabel(int index, Instances data) throws Exception {
StringBuffer text;
text = new StringBuffer();
text.append(((Instances) data).classAttribute().value(m_distribution.maxClass(index)));
text.append(" (" + Utils.roundDouble(m_distribution.perBag(index), 2));
if (Utils.gr(m_distribution.numIncorrect(index), 0))
text.append("/" + Utils.roundDouble(m_distribution.numIncorrect(index), 2));
text.append(")");
return text.toString();
}
/**
* Returns description of the boosted classifier.
*
* @return description of the boosted classifier as a string
*/
public String toString() {
// only ZeroR model?
if (m_ZeroR != null) {
StringBuffer buf = new StringBuffer();
buf.append(this.getClass().getName().replaceAll(".*\\.", "") + "\n");
buf.append(this.getClass().getName().replaceAll(".*\\.", "").replaceAll(".", "=") + "\n\n");
buf.append("Warning: No model could be built, hence ZeroR model is used:\n\n");
buf.append(m_ZeroR.toString());
return buf.toString();
}
StringBuffer text = new StringBuffer();
if (m_NumIterations == 0) {
text.append("MultiBoostAB: No model built yet.\n");
} else if (m_NumIterations == 1) {
text.append("MultiBoostAB: No boosting possible, one classifier used!\n");
text.append(m_Classifiers[0].toString() + "\n");
} else {
text.append("MultiBoostAB: Base classifiers and their weights: \n\n");
for (int i = 0; i < m_NumIterations; i++) {
if ((m_Classifiers != null) && (m_Classifiers[i] != null)) {
text.append(m_Classifiers[i].toString() + "\n\n");
text.append("Weight: " + Utils.roundDouble(m_Betas[i], 2) + "\n\n");
} else {
text.append("not yet initialized!\n\n");
}
}
text.append("Number of performed Iterations: " + m_NumIterations + "\n");
}
return text.toString();
}
