Module rusty_machine::learning::gp
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Gaussian Processes
Provides implementation of gaussian process regression.
Usage
use rusty_machine::learning::gp;
use rusty_machine::learning::SupModel;
use rusty_machine::linalg::Matrix;
use rusty_machine::linalg::Vector;
let mut gaussp = gp::GaussianProcess::default();
gaussp.noise = 10f64;
let train_data = Matrix::new(10,1,vec![0.,1.,2.,3.,4.,5.,6.,7.,8.,9.]);
let target = Vector::new(vec![0.,1.,2.,3.,4.,4.,3.,2.,1.,0.]);
gaussp.train(&train_data, &target).unwrap();
let test_data = Matrix::new(5,1,vec![2.3,4.4,5.1,6.2,7.1]);
let outputs = gaussp.predict(&test_data).unwrap();
Alternatively one could use gaussp.get_posterior()
which would return both
the predictive mean and covariance. However, this is likely to change in
a future release.
Structs
Constant mean function
Gaussian Process struct
Traits
Trait for GP mean functions.