Add significance level as parameter in best
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@ -271,7 +271,6 @@ namespace platform {
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}
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}
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void BestResults::reportAll(bool excel)
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void BestResults::reportAll(bool excel)
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{
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{
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double significance = 0.05;
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auto models = getModels();
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auto models = getModels();
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// Build the table of results
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// Build the table of results
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json table = buildTableResults(models);
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json table = buildTableResults(models);
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@ -7,7 +7,7 @@ using json = nlohmann::json;
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namespace platform {
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namespace platform {
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class BestResults {
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class BestResults {
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public:
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public:
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explicit BestResults(const string& path, const string& score, const string& model, bool friedman) : path(path), score(score), model(model), friedman(friedman) {}
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explicit BestResults(const string& path, const string& score, const string& model, bool friedman, double significance = 0.05) : path(path), score(score), model(model), friedman(friedman), significance(significance) {}
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string build();
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string build();
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void reportSingle();
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void reportSingle();
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void reportAll(bool excel);
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void reportAll(bool excel);
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@ -24,6 +24,7 @@ namespace platform {
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string score;
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string score;
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string model;
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string model;
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bool friedman;
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bool friedman;
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double significance;
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int maxModelName = 0;
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int maxModelName = 0;
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int maxDatasetName = 0;
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int maxDatasetName = 0;
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};
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};
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@ -15,6 +15,20 @@ argparse::ArgumentParser manageArguments(int argc, char** argv)
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program.add_argument("--report").help("report of best score results file").default_value(false).implicit_value(true);
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program.add_argument("--report").help("report of best score results file").default_value(false).implicit_value(true);
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program.add_argument("--friedman").help("Friedman test").default_value(false).implicit_value(true);
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program.add_argument("--friedman").help("Friedman test").default_value(false).implicit_value(true);
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program.add_argument("--excel").help("Output to excel").default_value(false).implicit_value(true);
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program.add_argument("--excel").help("Output to excel").default_value(false).implicit_value(true);
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program.add_argument("--level").help("significance level").default_value(0.05).scan<'g', double>().action([](const string& value) {
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try {
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auto k = stod(value);
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if (k < 0.01 || k > 0.15) {
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throw runtime_error("Significance level hast to be a number in [0.01, 0.15]");
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}
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return k;
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}
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catch (const runtime_error& err) {
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throw runtime_error(err.what());
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}
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catch (...) {
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throw runtime_error("Number of folds must be an decimal number");
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}});
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try {
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try {
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program.parse_args(argc, argv);
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program.parse_args(argc, argv);
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auto model = program.get<string>("model");
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auto model = program.get<string>("model");
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@ -23,6 +37,7 @@ argparse::ArgumentParser manageArguments(int argc, char** argv)
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auto report = program.get<bool>("report");
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auto report = program.get<bool>("report");
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auto friedman = program.get<bool>("friedman");
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auto friedman = program.get<bool>("friedman");
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auto excel = program.get<bool>("excel");
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auto excel = program.get<bool>("excel");
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auto level = program.get<double>("level");
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if (model == "" || score == "") {
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if (model == "" || score == "") {
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throw runtime_error("Model and score name must be supplied");
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throw runtime_error("Model and score name must be supplied");
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}
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}
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@ -59,7 +74,8 @@ int main(int argc, char** argv)
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auto report = program.get<bool>("report");
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auto report = program.get<bool>("report");
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auto friedman = program.get<bool>("friedman");
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auto friedman = program.get<bool>("friedman");
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auto excel = program.get<bool>("excel");
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auto excel = program.get<bool>("excel");
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auto results = platform::BestResults(platform::Paths::results(), score, model, friedman);
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auto level = program.get<double>("level");
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auto results = platform::BestResults(platform::Paths::results(), score, model, friedman, level);
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if (build) {
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if (build) {
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if (model == "any") {
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if (model == "any") {
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results.buildAll();
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results.buildAll();
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