public IOObject[] apply() throws OperatorException {
ExampleSet exampleSet = getInput(ExampleSet.class);
if (exampleSet.getAttributes().getLabel() == null) {
throw new UserError(this, 105);
}
if (!exampleSet.getAttributes().getLabel().isNominal()) {
throw new UserError(this, 101, "ROC Charts", exampleSet.getAttributes().getLabel());
}
if (exampleSet.getAttributes().getLabel().getMapping().getValues().size() != 2) {
throw new UserError(this, 114, "ROC Charts", exampleSet.getAttributes().getLabel());
}
if (exampleSet.getAttributes().getPredictedLabel() != null
&& getParameterAsBoolean(PARAMETER_USE_MODEL)) {
logWarning("Input example already has a predicted label which will be removed.");
PredictionModel.removePredictedLabel(exampleSet);
}
if (exampleSet.getAttributes().getPredictedLabel() == null
&& !getParameterAsBoolean(PARAMETER_USE_MODEL)) {
throw new UserError(this, 107);
}
Model model = null;
if (getParameterAsBoolean(PARAMETER_USE_MODEL)) {
model = getInput(Model.class);
exampleSet = model.apply(exampleSet);
}
if (exampleSet.getAttributes().getPredictedLabel() == null) {
throw new UserError(this, 107);
}
ROCDataGenerator rocDataGenerator = new ROCDataGenerator(1.0d, 1.0d);
ROCData rocPoints =
rocDataGenerator.createROCData(
exampleSet, getParameterAsBoolean(PARAMETER_USE_EXAMPLE_WEIGHTS));
rocDataGenerator.createROCPlotDialog(rocPoints);
PredictionModel.removePredictedLabel(exampleSet);
if (getParameterAsBoolean(PARAMETER_USE_MODEL)) {
return new IOObject[] {exampleSet, model};
} else return new IOObject[] {exampleSet};
}
@Override
public void doWork() throws OperatorException {
// sanity checks
ExampleSet exampleSet = exampleSetInput.getData(ExampleSet.class);
// checking preconditions
Attribute label = exampleSet.getAttributes().getLabel();
if (label == null) {
throw new UserError(this, 105);
}
if (!label.isNominal()) {
throw new UserError(this, 101, label, "threshold finding");
}
exampleSet.recalculateAttributeStatistics(label);
NominalMapping mapping = label.getMapping();
if (mapping.size() != 2) {
throw new UserError(
this,
118,
new Object[] {label, Integer.valueOf(mapping.getValues().size()), Integer.valueOf(2)});
}
if (exampleSet.getAttributes().getPredictedLabel() == null) {
throw new UserError(this, 107);
}
boolean useExplictLabels = getParameterAsBoolean(PARAMETER_DEFINE_LABELS);
double secondCost = getParameterAsDouble(PARAMETER_MISCLASSIFICATION_COSTS_SECOND);
double firstCost = getParameterAsDouble(PARAMETER_MISCLASSIFICATION_COSTS_FIRST);
if (useExplictLabels) {
String firstLabel = getParameterAsString(PARAMETER_FIRST_LABEL);
String secondLabel = getParameterAsString(PARAMETER_SECOND_LABEL);
if (mapping.getIndex(firstLabel) == -1) {
throw new UserError(this, 143, firstLabel, label.getName());
}
if (mapping.getIndex(secondLabel) == -1) {
throw new UserError(this, 143, secondLabel, label.getName());
}
// if explicit order differs from order in data: internally swap costs.
if (mapping.getIndex(firstLabel) > mapping.getIndex(secondLabel)) {
double temp = firstCost;
firstCost = secondCost;
secondCost = temp;
}
}
// check whether the confidence attributes are available
if (exampleSet.getAttributes().getConfidence(mapping.getPositiveString()) == null) {
throw new UserError(
this, 113, Attributes.CONFIDENCE_NAME + "_" + mapping.getPositiveString());
}
if (exampleSet.getAttributes().getConfidence(mapping.getNegativeString()) == null) {
throw new UserError(
this, 113, Attributes.CONFIDENCE_NAME + "_" + mapping.getNegativeString());
}
// create ROC data
ROCDataGenerator rocDataGenerator = new ROCDataGenerator(firstCost, secondCost);
ROCData rocData =
rocDataGenerator.createROCData(
exampleSet,
getParameterAsBoolean(PARAMETER_USE_EXAMPLE_WEIGHTS),
ROCBias.getROCBiasParameter(this));
// create plotter
if (getParameterAsBoolean(PARAMETER_SHOW_ROC_PLOT)) {
rocDataGenerator.createROCPlotDialog(rocData, true, true);
}
// create and return output
exampleSetOutput.deliver(exampleSet);
thresholdOutput.deliver(
new Threshold(
rocDataGenerator.getBestThreshold(),
mapping.getNegativeString(),
mapping.getPositiveString()));
}
