/* file: dbscan_dense_batch.cpp */
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!  Content:
!    C++ example of dense DBSCAN clustering in the batch processing mode

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

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

/* Input data set parameters */
string datasetFileName     = "../data/batch/dbscan_dense.csv";

/* DBSCAN algorithm parameters */
const float epsilon = 0.02f;
const size_t minObservations = 180;

int main(int argc, char *argv[])
    checkArguments(argc, argv, 1, &datasetFileName);

    /* Initialize FileDataSource to retrieve the input data from a .csv file */
    FileDataSource<CSVFeatureManager> dataSource(datasetFileName, DataSource::doAllocateNumericTable,

    /* Retrieve the data from the input file */

    /* Create an algorithm object for the DBSCAN algorithm */
    dbscan::Batch<> algorithm(epsilon, minObservations);

    algorithm.input.set(dbscan::data, dataSource.getNumericTable());


    /* Print the clusterization results */
    printNumericTable(algorithm.getResult()->get(dbscan::nClusters), "Number of clusters:");
    printNumericTable(algorithm.getResult()->get(dbscan::assignments), "Assignments of first 20 observations:", 20);

    return 0;
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