C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 3

minmax_dense_batch.cpp

/* 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);
dataSource.loadDataBlock();
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 */
algorithm.compute();
/* 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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