Developer Guide and Reference

  • 2021.4
  • 09/27/2021
  • Public Content
Contents

svm_reg_thunder_dense_batch.cpp

/******************************************************************************* * Copyright 2021 Intel Corporation * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *******************************************************************************/ #include "oneapi/dal/algo/svm.hpp" #include "oneapi/dal/io/csv.hpp" #include "example_util/utils.hpp" namespace dal = oneapi::dal; namespace svm = dal::svm; int main(int argc, char const *argv[]) { const auto train_data_file_name = get_data_path("svm_reg_train_dense_data.csv"); const auto train_response_file_name = get_data_path("svm_reg_train_dense_label.csv"); const auto test_data_file_name = get_data_path("svm_reg_test_dense_data.csv"); const auto test_response_file_name = get_data_path("svm_reg_test_dense_label.csv"); const auto x_train = dal::read<dal::table>(dal::csv::data_source{ train_data_file_name }); const auto y_train = dal::read<dal::table>(dal::csv::data_source{ train_response_file_name }); const auto kernel_desc = dal::linear_kernel::descriptor{}.set_scale(1.0).set_shift(0.0); const auto svm_desc = svm::descriptor<float, svm::method::thunder, svm::task::regression>{ kernel_desc } .set_c(100.0) .set_epsilon(0.3) .set_accuracy_threshold(0.001) .set_cache_size(200.0) .set_tau(1e-6); const auto result_train = dal::train(svm_desc, x_train, y_train); std::cout << "Biases:\n" << result_train.get_biases() << std::endl; std::cout << "Support indices:\n" << result_train.get_support_indices() << std::endl; const auto x_test = dal::read<dal::table>(dal::csv::data_source{ test_data_file_name }); const auto y_true = dal::read<dal::table>(dal::csv::data_source{ test_response_file_name }); const auto result_infer = dal::infer(svm_desc, result_train.get_model(), x_test); std::cout << "Responses result:\n" << result_infer.get_responses() << std::endl; std::cout << "Responses true:\n" << y_true << std::endl; return 0; }

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