public Measurement[] getModelMeasurements() {
List<Measurement> measurementList = new LinkedList<Measurement>();
measurementList.add(new Measurement("model training instances", trainingWeightSeenByModel()));
measurementList.add(new Measurement("model serialized size (bytes)", measureByteSize()));
Measurement[] modelMeasurements = getModelMeasurementsImpl();
if (modelMeasurements != null) {
for (Measurement measurement : modelMeasurements) {
measurementList.add(measurement);
}
}
// add average of sub-model measurements
Classifier[] subModels = getSubClassifiers();
if ((subModels != null) && (subModels.length > 0)) {
List<Measurement[]> subMeasurements = new LinkedList<Measurement[]>();
for (Classifier subModel : subModels) {
if (subModel != null) {
subMeasurements.add(subModel.getModelMeasurements());
}
}
Measurement[] avgMeasurements =
Measurement.averageMeasurements(
subMeasurements.toArray(new Measurement[subMeasurements.size()][]));
for (Measurement measurement : avgMeasurements) {
measurementList.add(measurement);
}
}
return measurementList.toArray(new Measurement[measurementList.size()]);
}
public void getDescription(StringBuilder out, int indent) {
StringUtils.appendIndented(out, indent, "Model type: ");
out.append(this.getClass().getName());
StringUtils.appendNewline(out);
Measurement.getMeasurementsDescription(getModelMeasurements(), out, indent);
StringUtils.appendNewlineIndented(out, indent, "Model description:");
StringUtils.appendNewline(out);
if (trainingHasStarted()) {
getModelDescription(out, indent);
} else {
StringUtils.appendIndented(out, indent, "Model has not been trained.");
}
}