Files
BayesNet/src/Platform/ReportBase.cc

114 lines
3.7 KiB
C++

#include <sstream>
#include <locale>
#include "Datasets.h"
#include "ReportBase.h"
#include "BestScore.h"
namespace platform {
ReportBase::ReportBase(json data_, bool compare) : data(data_), compare(compare), margin(0.1)
{
stringstream oss;
oss << "Better than ZeroR + " << setprecision(1) << fixed << margin * 100 << "%";
meaning = {
{Symbols::equal_best, "Equal to best"},
{Symbols::better_best, "Better than best"},
{Symbols::cross, "Less than or equal to ZeroR"},
{Symbols::upward_arrow, oss.str()}
};
}
string ReportBase::fromVector(const string& key)
{
stringstream oss;
string sep = "";
oss << "[";
for (auto& item : data[key]) {
oss << sep << item.get<double>();
sep = ", ";
}
oss << "]";
return oss.str();
}
string ReportBase::fVector(const string& title, const json& data, const int width, const int precision)
{
stringstream oss;
string sep = "";
oss << title << "[";
for (const auto& item : data) {
oss << sep << fixed << setw(width) << setprecision(precision) << item.get<double>();
sep = ", ";
}
oss << "]";
return oss.str();
}
void ReportBase::show()
{
header();
body();
}
string ReportBase::compareResult(const string& dataset, double result)
{
string status = " ";
if (compare) {
double best = bestResult(dataset, data["model"].get<string>());
if (result == best) {
status = Symbols::equal_best;
} else if (result > best) {
status = Symbols::better_best;
}
} else {
if (data["score_name"].get<string>() == "accuracy") {
auto dt = Datasets(Paths::datasets(), false);
dt.loadDataset(dataset);
auto numClasses = dt.getNClasses(dataset);
if (numClasses == 2) {
vector<int> distribution = dt.getClassesCounts(dataset);
double nSamples = dt.getNSamples(dataset);
vector<int>::iterator maxValue = max_element(distribution.begin(), distribution.end());
double mark = *maxValue / nSamples * (1 + margin);
if (mark > 1) {
mark = 0.9995;
}
status = result < mark ? Symbols::cross : result > mark ? Symbols::upward_arrow : "=";
}
}
}
if (status != " ") {
auto item = summary.find(status);
if (item != summary.end()) {
summary[status]++;
} else {
summary[status] = 1;
}
}
return status;
}
double ReportBase::bestResult(const string& dataset, const string& model)
{
double value = 0.0;
if (bestResults.size() == 0) {
// try to load the best results
string score = data["score_name"];
replace(score.begin(), score.end(), '_', '-');
string fileName = "best_results_" + score + "_" + model + ".json";
ifstream resultData(Paths::results() + "/" + fileName);
if (resultData.is_open()) {
bestResults = json::parse(resultData);
} else {
existBestFile = false;
}
}
try {
value = bestResults.at(dataset).at(0);
}
catch (exception) {
value = 1.0;
}
return value;
}
bool ReportBase::getExistBestFile()
{
return existBestFile;
}
}