GaussianProcessTreegp¶
- class lsst.meas.algorithms.GaussianProcessTreegp(std=1.0, correlation_length=1.0, white_noise=0.0, mean=0.0)¶
- Bases: - object- Gaussian Process Treegp class for Gaussian Process interpolation. - The basic GP regression, which uses Cholesky decomposition. - Methods Summary - fit(x_train, y_train)- Fit the Gaussian Process to the given training data. - predict(x_predict)- Predict the target values for the given input features. - Methods Documentation - fit(x_train, y_train)¶
- Fit the Gaussian Process to the given training data. 
 - predict(x_predict)¶
- Predict the target values for the given input features.