use rm::linalg::Matrix; | |
use rm::linalg::Vector; | |
use rm::learning::SupModel; | |
use rm::learning::gp::GaussianProcess; | |
#[test] | |
fn test_default_gp() { | |
let mut gp = GaussianProcess::default(); | |
gp.noise = 10f64; | |
let inputs = Matrix::new(10,1,vec![0.,1.,2.,3.,4.,5.,6.,7.,8.,9.]); | |
let targets = Vector::new(vec![0.,1.,2.,3.,4.,4.,3.,2.,1.,0.]); | |
gp.train(&inputs, &targets).unwrap(); | |
let test_inputs = Matrix::new(5,1,vec![2.3,4.4,5.1,6.2,7.1]); | |
let _outputs = gp.predict(&test_inputs).unwrap(); | |
} |