rmontanana/BayesNet
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Complete first step

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This commit is contained in:
Ricardo Montañana Gómez
2023-11-23 12:59:21 +01:00
parent bbe5302ab1
commit 8b7b59d42b
4 changed files with 38 additions and 8 deletions
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28
src/Platform/GridSearch.cc
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@@ -36,7 +36,7 @@ namespace platform {
return Colors::RESET();
}
}
void GridSearch::processFile(std::string fileName, Datasets& datasets, HyperParameters& hyperparameters)
double GridSearch::processFile(std::string fileName, Datasets& datasets, HyperParameters& hyperparameters)
{
// Get dataset
auto [X, y] = datasets.getTensors(fileName);
@@ -44,6 +44,8 @@ namespace platform {
auto features = datasets.getFeatures(fileName);
auto samples = datasets.getNSamples(fileName);
auto className = datasets.getClassName(fileName);
double totalScore = 0.0;
int numItems = 0;
for (const auto& seed : config.seeds) {
std::cout << "(" << seed << ") doing Fold: " << flush;
Fold* fold;
@@ -51,8 +53,10 @@ namespace platform {
fold = new StratifiedKFold(config.n_folds, y, seed);
else
fold = new KFold(config.n_folds, y.size(0), seed);
double bestScore = 0.0;
for (int nfold = 0; nfold < config.n_folds; nfold++) {
auto clf = Models::instance()->create(config.model);
clf->setHyperparameters(hyperparameters.get(fileName));
auto [train, test] = fold->getFold(nfold);
auto train_t = torch::tensor(train);
auto test_t = torch::tensor(test);
@@ -60,15 +64,18 @@ namespace platform {
auto y_train = y.index({ train_t });
auto X_test = X.index({ "...", test_t });
auto y_test = y.index({ test_t });
showProgressFold(nfold + 1, getColor(clf->getStatus()), "a");
// Train model
// clf->fit(X_train, y_train, features, className, states);
clf->fit(X_train, y_train, features, className, states);
showProgressFold(nfold + 1, getColor(clf->getStatus()), "a");
showProgressFold(nfold + 1, getColor(clf->getStatus()), "b");
totalScore += clf->score(X_test, y_test);
numItems++;
showProgressFold(nfold + 1, getColor(clf->getStatus()), "c");
std::cout << "\b\b\b, \b" << flush;
}
delete fold;
}
return numItems == 0 ? 0.0 : totalScore / numItems;
}
void GridSearch::go()
{
@@ -83,12 +90,21 @@ namespace platform {
for (const auto& dataset : datasets.getNames()) {
std::cout << "- " << setw(20) << left << dataset << " " << right << flush;
int num = 0;
double bestScore = 0.0;
json bestHyperparameters;
for (const auto& hyperparam_line : grid.getGrid(config.model)) {
showProgressComb(++num, totalComb, Colors::CYAN());
auto hyperparameters = platform::HyperParameters(datasets.getNames(), hyperparam_line);
processFile(dataset, datasets, hyperparameters);
double score = processFile(dataset, datasets, hyperparameters);
if (score > bestScore) {
bestScore = score;
bestHyperparameters = hyperparam_line;
}
}
std::cout << "end." << std::endl;
std::cout << "end." << " Score: " << setw(9) << setprecision(7) << fixed
<< bestScore << " [" << bestHyperparameters.dump() << "]" << std::endl;
results[dataset]["score"] = bestScore;
results[dataset]["hyperparameters"] = bestHyperparameters;
}
// Save results
save();
@@ -96,7 +112,7 @@ namespace platform {
void GridSearch::save()
{
std::ofstream file(config.output_file);
// file << results.dump(4);
file << results.dump(4);
file.close();
}
} /* namespace platform */