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Fix xgboost error in predict/predict_proba

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Ricardo Montañana Gómez
2025-04-12 17:48:23 +02:00
parent 761f57be6c
commit 830265d91b
4 changed files with 55 additions and 30 deletions
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45
tests/TestPythonClassifiers.cc
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@@ -116,23 +116,30 @@ TEST_CASE("XGBoost", "[PyClassifiers]")
clf.setHyperparameters(hyperparameters);
auto score = clf.score(raw.Xt, raw.yt);
REQUIRE(score == Catch::Approx(0.98).epsilon(raw.epsilon));
std::cout << "XGBoost score: " << score << std::endl;
}
// TEST_CASE("XGBoost predict proba", "[PyClassifiers]")
// {
// auto raw = RawDatasets("iris", true);
// auto clf = pywrap::XGBoost();
// clf.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, raw.statest);
// // nlohmann::json hyperparameters = { "n_jobs=1" };
// // clf.setHyperparameters(hyperparameters);
// auto predict = clf.predict(raw.Xt);
// for (int row = 0; row < predict.size(0); row++) {
// auto sum = 0.0;
// for (int col = 0; col < predict.size(1); col++) {
// std::cout << std::setw(12) << std::setprecision(10) << predict[row][col].item<double>() << " ";
// sum += predict[row][col].item<int>();
// }
// std::cout << std::endl;
// // REQUIRE(sum == Catch::Approx(1.0).epsilon(raw.epsilon));
// }
// std::cout << predict << std::endl;
// }
TEST_CASE("XGBoost predict proba", "[PyClassifiers]")
{
auto raw = RawDatasets("iris", true);
auto clf = pywrap::XGBoost();
clf.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, raw.statest);
// nlohmann::json hyperparameters = { "n_jobs=1" };
// clf.setHyperparameters(hyperparameters);
auto predict_proba = clf.predict_proba(raw.Xt);
auto predict = clf.predict(raw.Xt);
// std::cout << "Predict proba: " << predict_proba << std::endl;
// std::cout << "Predict proba size: " << predict_proba.sizes() << std::endl;
// assert(predict.size(0) == predict_proba.size(0));
for (int row = 0; row < predict_proba.size(0); row++) {
// auto sum = 0.0;
// std::cout << "Row " << std::setw(3) << row << ": ";
// for (int col = 0; col < predict_proba.size(1); col++) {
// std::cout << std::setw(9) << std::fixed << std::setprecision(7) << predict_proba[row][col].item<double>() << " ";
// sum += predict_proba[row][col].item<double>();
// }
// std::cout << " -> " << std::setw(9) << std::fixed << std::setprecision(7) << sum << " -> " << torch::argmax(predict_proba[row]).item<int>() << " = " << predict[row].item<int>() << std::endl;
// // REQUIRE(sum == Catch::Approx(1.0).epsilon(raw.epsilon));
REQUIRE(torch::argmax(predict_proba[row]).item<int>() == predict[row].item<int>());
REQUIRE(torch::sum(predict_proba[row]).item<double>() == Catch::Approx(1.0).epsilon(raw.epsilon));
}
}