C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 1

kernel_func_lin_csr_batch.cpp

/* file: kernel_func_lin_csr_batch.cpp */
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/*
! Content:
! C++ example of computing a linear kernel function 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 leftDatasetFileName = "../data/batch/kernel_function_csr.csv";
string rightDatasetFileName = "../data/batch/kernel_function_csr.csv";
/* Kernel algorithm parameters */
const double k = 1.0; /* Linear kernel coefficient in the k(X,Y) + b model */
const double b = 0.0; /* Linear kernel coefficient in the k(X,Y) + b model */
int main(int argc, char *argv[])
{
checkArguments(argc, argv, 1, &leftDatasetFileName);
checkArguments(argc, argv, 1, &rightDatasetFileName);
/* Read datasetFileName from a file and create a numeric tables to store input data */
CSRNumericTablePtr leftData(createSparseTable<float>(leftDatasetFileName));
CSRNumericTablePtr rightData(createSparseTable<float>(rightDatasetFileName));
/* Create algorithm objects for the kernel algorithm using the default method */
kernel_function::linear::Batch<float, kernel_function::linear::fastCSR> algorithm;
/* Set the kernel algorithm parameter */
algorithm.parameter.k = k;
algorithm.parameter.b = b;
algorithm.parameter.computationMode = kernel_function::matrixMatrix;
/* Set an input data table for the algorithm */
algorithm.input.set(kernel_function::X, leftData);
algorithm.input.set(kernel_function::Y, rightData);
/* Compute the linear kernel function */
algorithm.compute();
/* Get the computed results */
kernel_function::ResultPtr result = algorithm.getResult();
/* Print the results */
printNumericTable(result->get(kernel_function::values), "Values");
return 0;
}

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