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Refactor arguments management for Experimentation

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This commit is contained in:
Ricardo Montañana Gómez
2025-01-18 18:26:34 +01:00
parent 7aaf6d1bf8
commit 3397d0962f
10 changed files with 325 additions and 420 deletions
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26
src/main/Experiment.h
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@@ -20,7 +20,6 @@ namespace platform {
Experiment& setTitle(const std::string& title) { this->result.setTitle(title); return *this; }
Experiment& setModelVersion(const std::string& model_version) { this->result.setModelVersion(model_version); return *this; }
Experiment& setModel(const std::string& model) { this->result.setModel(model); return *this; }
std::string getModel() const { return result.getModel(); }
Experiment& setLanguage(const std::string& language) { this->result.setLanguage(language); return *this; }
Experiment& setDiscretizationAlgorithm(const std::string& discretization_algo)
{
@@ -28,7 +27,8 @@ namespace platform {
}
Experiment& setSmoothSrategy(const std::string& smooth_strategy)
{
this->smooth_strategy = smooth_strategy; this->result.setSmoothStrategy(smooth_strategy);
this->smooth_strategy = smooth_strategy;
this->result.setSmoothStrategy(smooth_strategy);
if (smooth_strategy == "ORIGINAL")
smooth_type = bayesnet::Smoothing_t::ORIGINAL;
else if (smooth_strategy == "LAPLACE")
@@ -50,18 +50,32 @@ namespace platform {
Experiment& setDuration(float duration) { this->result.setDuration(duration); return *this; }
Experiment& setHyperparameters(const HyperParameters& hyperparameters_) { this->hyperparameters = hyperparameters_; return *this; }
HyperParameters& getHyperParameters() { return hyperparameters; }
void cross_validation(const std::string& fileName, bool quiet, bool no_train_score, bool generate_fold_files, bool graph);
void go(std::vector<std::string> filesToProcess, bool quiet, bool no_train_score, bool generate_fold_files, bool graph);
std::string getModel() const { return result.getModel(); }
std::string getScore() const { return result.getScoreName(); }
bool isDiscretized() const { return discretized; }
bool isStratified() const { return stratified; }
bool isQuiet() const { return quiet; }
std::string getSmoothStrategy() const { return smooth_strategy; }
int getNFolds() const { return nfolds; }
std::vector<int> getRandomSeeds() const { return randomSeeds; }
void cross_validation(const std::string& fileName);
void go();
void saveResult();
void show();
void saveGraph();
void report(bool classification_report = false);
void report();
void setFilesToTest(const std::vector<std::string>& filesToTest) { this->filesToTest = filesToTest; }
void setQuiet(bool quiet) { this->quiet = quiet; }
void setNoTrainScore(bool no_train_score) { this->no_train_score = no_train_score; }
void setGenerateFoldFiles(bool generate_fold_files) { this->generate_fold_files = generate_fold_files; }
void setGraph(bool graph) { this->graph = graph; }
private:
score_t parse_score() const;
Result result;
bool discretized{ false }, stratified{ false };
bool discretized{ false }, stratified{ false }, generate_fold_files{ false }, graph{ false }, quiet{ false }, no_train_score{ false };
std::vector<PartialResult> results;
std::vector<int> randomSeeds;
std::vector<std::string> filesToTest;
std::string discretization_algo;
std::string smooth_strategy;
bayesnet::Smoothing_t smooth_type{ bayesnet::Smoothing_t::NONE };