/**
* Calculates the performance stats for the desired class and return results as a set of
* Instances.
*
* @param predictions the predictions to base the curve on
* @param classIndex index of the class of interest.
* @return datapoints as a set of instances.
*/
public Instances getCurve(FastVector predictions, int classIndex) {
if ((predictions.size() == 0)
|| (((NominalPrediction) predictions.elementAt(0)).distribution().length <= classIndex)) {
return null;
}
ThresholdCurve tc = new ThresholdCurve();
Instances threshInst = tc.getCurve(predictions, classIndex);
Instances insts = makeHeader();
int fpind = threshInst.attribute(ThresholdCurve.FP_RATE_NAME).index();
int tpind = threshInst.attribute(ThresholdCurve.TP_RATE_NAME).index();
int threshind = threshInst.attribute(ThresholdCurve.THRESHOLD_NAME).index();
double[] vals;
double fpval, tpval, thresh;
for (int i = 0; i < threshInst.numInstances(); i++) {
fpval = threshInst.instance(i).value(fpind);
tpval = threshInst.instance(i).value(tpind);
thresh = threshInst.instance(i).value(threshind);
vals = new double[3];
vals[0] = 0;
vals[1] = fpval;
vals[2] = thresh;
insts.add(new Instance(1.0, vals));
vals = new double[3];
vals[0] = 1;
vals[1] = 1.0 - tpval;
vals[2] = thresh;
insts.add(new Instance(1.0, vals));
}
return insts;
}
/**
* Finds residuals (squared) for the current regression.
*
* @throws Exception if an error occurs
*/
private void findResiduals() throws Exception {
m_SSR = 0;
m_Residuals = new double[m_Data.numInstances()];
for (int i = 0; i < m_Data.numInstances(); i++) {
m_Residuals[i] = m_currentRegression.classifyInstance(m_Data.instance(i));
m_Residuals[i] -= m_Data.instance(i).value(m_Data.classAttribute());
m_Residuals[i] *= m_Residuals[i];
m_SSR += m_Residuals[i];
}
}
/**
* Signify that this batch of input to the filter is finished. If the filter requires all
* instances prior to filtering, output() may now be called to retrieve the filtered instances.
*
* @return true if there are instances pending output
* @exception Exception if an error occurs
* @exception IllegalStateException if no input structure has been defined
*/
public boolean batchFinished() throws Exception {
if (getInputFormat() == null) {
throw new IllegalStateException("No input instance format defined");
}
if (m_Means == null) {
Instances input = getInputFormat();
m_Means = new double[input.numAttributes()];
m_StdDevs = new double[input.numAttributes()];
for (int i = 0; i < input.numAttributes(); i++) {
if (input.attribute(i).isNumeric() && (input.classIndex() != i)) {
m_Means[i] = input.meanOrMode(i);
m_StdDevs[i] = Math.sqrt(input.variance(i));
}
}
// Convert pending input instances
for (int i = 0; i < input.numInstances(); i++) {
convertInstance(input.instance(i));
}
}
// Free memory
flushInput();
m_NewBatch = true;
return (numPendingOutput() != 0);
}
