rmontanana/BayesNet
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Add significance level as parameter in best

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This commit is contained in:
Ricardo Montañana Gómez 2023-10-02 15:46:40 +02:00
parent 57c27f739c
commit 93e4ff94db
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
3 changed files with 19 additions and 3 deletions
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1
src/Platform/BestResults.cc
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@ -271,7 +271,6 @@ namespace platform {
}
void BestResults::reportAll(bool excel)
{
double significance = 0.05;
auto models = getModels();
// Build the table of results
json table = buildTableResults(models);

3
src/Platform/BestResults.h
View File

@ -7,7 +7,7 @@ using json = nlohmann::json;
namespace platform {
class BestResults {
public:
explicit BestResults(const string& path, const string& score, const string& model, bool friedman) : path(path), score(score), model(model), friedman(friedman) {}
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) {}
string build();
void reportSingle();
void reportAll(bool excel);
@ -24,6 +24,7 @@ namespace platform {
string score;
string model;
bool friedman;
double significance;
int maxModelName = 0;
int maxDatasetName = 0;
};

18
src/Platform/best.cc
View File

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