/* file: minmax_dense_batch.cpp */
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!  Content:
!    C++ example of min-max normalization algorithm.

#include "daal.h"
#include "service.h"

using namespace std;
using namespace daal;
using namespace daal::algorithms;
using namespace daal::algorithms::normalization;

/* Input data set parameters */
string datasetName = "../data/batch/normalization.csv";

int main()
    /* Retrieve the input data */
    FileDataSource<CSVFeatureManager> dataSource(datasetName, DataSource::doAllocateNumericTable, DataSource::doDictionaryFromContext);

    NumericTablePtr data = dataSource.getNumericTable();

    /* Create an algorithm */
    minmax::Batch<float, minmax::defaultDense> algorithm;

    /* Set lower and upper bounds for the algorithm */
    algorithm.parameter.lowerBound = -1.0;
    algorithm.parameter.upperBound =  1.0;

    /* Set an input object for the algorithm */
    algorithm.input.set(minmax::data, data);

    /* Compute min-max normalization function */

    /* Print the results of stage */
    minmax::ResultPtr res = algorithm.getResult();

    printNumericTable(data, "First 10 rows of the input data:", 10);
    printNumericTable(res->get(minmax::normalizedData), "First 10 rows of the min-max normalization result:", 10);

    return 0;
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