public void increment(double x, Object y) {
KernelRegression kreg;
double score;
// increment all categories
for (Object o : kernelRegressionMap.keySet()) {
kreg = kernelRegressionMap.get(o);
score = itemScoring.computeCategoryScore(o, y);
kreg.increment(x, score);
}
// increment item
score = itemScoring.computeItemScore(y);
expectedScore.increment(x, score);
}
public void initializeCategories() {
expectedScore = new KernelRegression(kernel, bandwidth, uniform);
// add all categories to map
Iterator<Object> iter = itemScoring.categoryIterator();
Object obj = null;
while (iter.hasNext()) {
obj = iter.next();
kernelRegressionMap.put(obj, new KernelRegression(kernel, bandwidth, uniform));
}
}
public double getMaximumPossibleScore() {
return itemScoring.maximumPossibleScore();
}
public double getScoreValue(Object category) {
return itemScoring.computeItemScore(category);
}
