Compute your R 'neuralnet' neural network using cpp code.
You can train you neural network with R:
> library( 'neuralnet' ) > data <- data.frame( i1 = c(1, 2, 4), i2 = c(5, 5, 6), o = c(1, 1, 0) ) > net <- neuralnet( o~i1+i2, hidden = c( 5, 2 ) )
Then test your net:
> test <- data.frame( i1 = 5, i2 = 1 )
> res <- compute( net, test )
> res$net.result
[,1]
[1,] -0.08056605515
And convert that network into cpp:
> compute.gen.cpp( net, "~/myprojects/subfolder/compute.cpp" )
Test your network using compute.cpp:
int main(int argc, char *argv[])
{
const double covariates[2] = { 5, 1 };
double results[1] = { 0 };
neuralnet::compute( &covariates[0], &results[0] );
printf( "%f\n", results[0] ); // -0.080566
return 0;
}