336f8e11c48bb4e749b9f389907c450e44f02786,GPy/examples/regression.py,,toy_poisson_rbf_1d,#Any#Any#,273

Before Change


    X = np.linspace(0,10)[:, None]
    F = np.round(X*3-4)
    F = np.where(F > 0, F, 0)
    eps = np.random.randint(0,4, F.shape[0])[:, None]
    Y = F + eps

    noise_model = GPy.likelihoods.poisson()

After Change


    Run a simple demonstration of a standard Gaussian process fitting it to data sampled from an RBF covariance.
    x_len = 400
    X = np.linspace(0, 10, x_len)[:, None]
    f_true = np.random.multivariate_normal(np.zeros(x_len), GPy.kern.rbf(1).K(X))
    Y = np.array([np.random.poisson(np.exp(f)) for f in f_true])[:,None]

    noise_model = GPy.likelihoods.poisson()
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: SheffieldML/GPy
Commit Name: 336f8e11c48bb4e749b9f389907c450e44f02786
Time: 2013-10-28
Author: alan.daniel.saul@gmail.com
File Name: GPy/examples/regression.py
Class Name:
Method Name: toy_poisson_rbf_1d


Project Name: SheffieldML/GPy
Commit Name: 336f8e11c48bb4e749b9f389907c450e44f02786
Time: 2013-10-28
Author: alan.daniel.saul@gmail.com
File Name: GPy/examples/regression.py
Class Name:
Method Name: toy_poisson_rbf_1d_laplace


Project Name: scipy/scipy
Commit Name: f635a41267a02ffa75dc6b8890d5585d018b1359
Time: 2007-04-10
Author: jtravs@localhost
File Name: Lib/sandbox/rbf/tests/test_rbf.py
Class Name: test_Rbf2D
Method Name: check_multiquadrics