public List<TrainAndTestReportCrisp> computeAvgCTSperM(List<TrainAndTestReportCrisp> reportsCTS) {
weightsCrisp.clear();
weightsInterval.clear();
Map<Model, List<TrainAndTestReportCrisp>> mapForAvg = new HashMap<>();
for (TrainAndTestReportCrisp r : reportsCTS) {
if (mapForAvg.containsKey(r.getModel())) {
mapForAvg.get(r.getModel()).add(r);
} else {
List<TrainAndTestReportCrisp> l = new ArrayList<>();
l.add(r);
mapForAvg.put(r.getModel(), l);
}
}
List<TrainAndTestReportCrisp> avgReports = new ArrayList<>();
for (Model model : mapForAvg.keySet()) {
List<TrainAndTestReportCrisp> l = mapForAvg.get(model);
if (l.size() == 1) { // does not make sense to compute average over one series
// do not compute anything
} else {
TrainAndTestReportCrisp thisAvgReport = computeAvgCTS(l, model);
if (thisAvgReport != null) {
avgReports.add(thisAvgReport);
} else { // should never happen for the same method
System.err.println("nerovnake percenttrain v ramci 1 modelu pri avg CTS per method :/");
}
}
}
return avgReports;
}
