@Override
public double getLoss(
List<? extends AbstractInstance> crossValSet, PredictiveModel predictiveModel) {
Auc auc = new Auc();
for (AbstractInstance instance : crossValSet) {
auc.add(
(Double) instance.getClassification() == 1.0 ? 1 : 0,
predictiveModel.getProbability(instance.getAttributes(), 1.0));
}
return 1 - auc.auc();
}
private static HashMap<String, ClicksAndImps> uniqueBrowserDataPredicted(
PredictiveModel predictiveModel, List<Instance> instances) {
HashMap<String, ClicksAndImps> uniqueBrowsers = new HashMap<>();
for (Instance instance : instances) {
String browser = (String) instance.getAttributes().get("an_browser");
double clickProb =
Utils.correctProbability(
.99, predictiveModel.getProbability(instance.getAttributes(), 1.0));
if (browser != null) {
int count = 0;
if (!uniqueBrowsers.containsKey(browser)) {
uniqueBrowsers.put(browser, new ClicksAndImps());
}
uniqueBrowsers.get(browser).imps++;
uniqueBrowsers.get(browser).clicks += clickProb;
}
}
for (String key : uniqueBrowsers.keySet()) {
uniqueBrowsers.get(key).setCtr();
}
return uniqueBrowsers;
}
