diff --git a/README.md b/README.md index 5e5172d..05d5749 100644 --- a/README.md +++ b/README.md @@ -2,6 +2,7 @@ ![C++](https://img.shields.io/badge/c++-%2300599C.svg?style=flat&logo=c%2B%2B&logoColor=white) [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)]() +[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/rmontanana/Platform) ![Gitea Last Commit](https://img.shields.io/gitea/last-commit/rmontanana/platform?gitea_url=https://gitea.rmontanana.es&logo=gitea) Platform to run Bayesian Networks and Machine Learning Classifiers experiments. diff --git a/src/commands/b_best.cpp b/src/commands/b_best.cpp index 39ec19a..970ff1f 100644 --- a/src/commands/b_best.cpp +++ b/src/commands/b_best.cpp @@ -9,9 +9,8 @@ void manageArguments(argparse::ArgumentParser& program) { - program.add_argument("-m", "--model") - .help("Model to use or any") - .default_value("any"); + program.add_argument("-m", "--model").help("Model to use or any").default_value("any"); + program.add_argument("--folder").help("Results folder to use").default_value(platform::Paths::results()); program.add_argument("-d", "--dataset").default_value("any").help("Filter results of the selected model) (any for all datasets)"); program.add_argument("-s", "--score").default_value("accuracy").help("Filter results of the score name supplied"); program.add_argument("--friedman").help("Friedman test").default_value(false).implicit_value(true); @@ -38,12 +37,13 @@ int main(int argc, char** argv) { argparse::ArgumentParser program("b_best", { platform_project_version.begin(), platform_project_version.end() }); manageArguments(program); - std::string model, dataset, score; + std::string model, dataset, score, folder; bool build, report, friedman, excel, tex, index; double level; try { program.parse_args(argc, argv); model = program.get("model"); + folder = program.get("folder"); dataset = program.get("dataset"); score = program.get("score"); friedman = program.get("friedman"); @@ -66,7 +66,7 @@ int main(int argc, char** argv) exit(1); } // Generate report - auto results = platform::BestResults(platform::Paths::results(), score, model, dataset, friedman, level); + auto results = platform::BestResults(folder, score, model, dataset, friedman, level); if (model == "any") { results.buildAll(); results.reportAll(excel, tex, index); diff --git a/src/experimental_clfs/ExpClf.h b/src/experimental_clfs/ExpClf.h index fc6d3ec..dbb2140 100644 --- a/src/experimental_clfs/ExpClf.h +++ b/src/experimental_clfs/ExpClf.h @@ -43,6 +43,7 @@ namespace platform { void add_active_parents(const std::vector& active_parents); void add_active_parent(int parent); void remove_last_parent(); + void setHyperparameters(const nlohmann::json& hyperparameters_) override {}; protected: bool debug = false; Xaode aode_; diff --git a/src/main/Experiment.cpp b/src/main/Experiment.cpp index 0c2c39a..3e33e28 100644 --- a/src/main/Experiment.cpp +++ b/src/main/Experiment.cpp @@ -270,7 +270,6 @@ namespace platform { // if (!quiet) showProgress(nfold + 1, getColor(clf->getStatus()), "c"); - std::cout << "Discretized: " << discretized << " " << score_train_value << std::endl; test_timer.start(); // auto y_predict = clf->predict(X_test); auto y_proba_test = clf->predict_proba(X_test);