* Wait for package installation.
     */
    public void wait_install();
};

            

Reported by PMD.

                   * @param callback answer object with approve and cancel methods and the package description.
     */
    public void onPackageInstall(final int operation, InstallCallbackInterface callback);
};

            

Reported by PMD.

              
#include <emscripten/bind.h>

@INCLUDES@
#include "../../../modules/core/src/parallel_impl.hpp"

#ifdef TEST_WASM_INTRIN
#include "../../../modules/core/include/opencv2/core/hal/intrin.hpp"
#include "../../../modules/core/include/opencv2/core/utils/trace.hpp"

            

Reported by Cppcheck.

                      return covMatType;
    }

    EMImpl()
    {
        nclusters = DEFAULT_NCLUSTERS;
        covMatType=EM::COV_MAT_DIAGONAL;
        termCrit = TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, EM::DEFAULT_MAX_ITERS, 1e-6);
    }

            

Reported by Cppcheck.

                  }
}

INSTANTIATE_TEST_CASE_P(/**/, ML_ANN_Params, testing::ValuesIn(activation_list));

//==================================================================================================

CV_ENUM(ANN_MLP_METHOD, ANN_MLP::RPROP, ANN_MLP::ANNEAL)


            

Reported by Cppcheck.

                  }
}

INSTANTIATE_TEST_CASE_P(/**/, ML_EM_Params,
    testing::Combine(
        testing::Values(EM::START_AUTO_STEP, EM::START_M_STEP, EM::START_E_STEP),
        testing::Values(EM::COV_MAT_GENERIC, EM::COV_MAT_DIAGONAL, EM::COV_MAT_SPHERICAL)
    ));


            

Reported by Cppcheck.

              using cv::ml::EM;
using cv::ml::KNearest;

TEST(ML_KNearest, accuracy)
{
    int sizesArr[] = { 500, 700, 800 };
    int pointsCount = sizesArr[0]+ sizesArr[1] + sizesArr[2];

    Mat trainData( pointsCount, 2, CV_32FC1 ), trainLabels;

            

Reported by Cppcheck.

              
//==================================================================================================

TEST(ML_LR, save_load)
{
    string dataFileName = findDataFile("iris.data");
    Ptr<TrainData> tdata = TrainData::loadFromCSV(dataFileName, 0);
    ASSERT_FALSE(tdata.empty());
    Mat responses1, responses2;

            

Reported by Cppcheck.

                  EXPECT_NEAR(err, param.mean, 4 * param.sigma);
}

INSTANTIATE_TEST_CASE_P(/**/, ML_Params, testing::ValuesIn(ML_Params_List));


//==================================================================================================

struct ML_SL_Params_t

            

Reported by Cppcheck.

                  EXPECT_EQ(result.at<float>(0, predicted_class), rt->predict(test));
}

TEST(ML_RTrees, 11142_sample_weights_regression)
{
    int n = 3;
    // RTrees for regression
    Ptr<ml::RTrees> rt = cv::ml::RTrees::create();
    //simple regression problem of x -> 2x

            

Reported by Cppcheck.