public void textValueChanged(TextEvent e) {
((TextListener) a).textValueChanged(e);
((TextListener) b).textValueChanged(e);
}
@Override
protected void notifyJobOutputListeners() {
weka.classifiers.Classifier finalClassifier =
((weka.distributed.spark.WekaClassifierSparkJob) m_runningJob).getClassifier();
Instances modelHeader =
((weka.distributed.spark.WekaClassifierSparkJob) m_runningJob).getTrainingHeader();
String classAtt =
((weka.distributed.spark.WekaClassifierSparkJob) m_runningJob).getClassAttribute();
try {
weka.distributed.spark.WekaClassifierSparkJob.setClassIndex(classAtt, modelHeader, true);
} catch (Exception ex) {
if (m_log != null) {
m_log.logMessage(statusMessagePrefix() + ex.getMessage());
}
ex.printStackTrace();
}
if (finalClassifier == null) {
if (m_log != null) {
m_log.logMessage(statusMessagePrefix() + "No classifier produced!");
}
}
if (modelHeader == null) {
if (m_log != null) {
m_log.logMessage(statusMessagePrefix() + "No training header available for the model!");
}
}
if (finalClassifier != null) {
if (m_textListeners.size() > 0) {
String textual = finalClassifier.toString();
String title = "Spark: ";
String classifierSpec = finalClassifier.getClass().getName();
if (finalClassifier instanceof OptionHandler) {
classifierSpec += " " + Utils.joinOptions(((OptionHandler) finalClassifier).getOptions());
}
title += classifierSpec;
TextEvent te = new TextEvent(this, textual, title);
for (TextListener t : m_textListeners) {
t.acceptText(te);
}
}
if (modelHeader != null) {
// have to add a single bogus instance to the header to trick
// the SerializedModelSaver into saving it (since it ignores
// structure only DataSetEvents) :-)
double[] vals = new double[modelHeader.numAttributes()];
for (int i = 0; i < vals.length; i++) {
vals[i] = Utils.missingValue();
}
Instance tempI = new DenseInstance(1.0, vals);
modelHeader.add(tempI);
DataSetEvent dse = new DataSetEvent(this, modelHeader);
BatchClassifierEvent be = new BatchClassifierEvent(this, finalClassifier, dse, dse, 1, 1);
for (BatchClassifierListener b : m_classifierListeners) {
b.acceptClassifier(be);
}
}
}
}
