Modifying Old GaussianProcessor Example To Run With GaussianProcessRegressor

I have an example from a data science book I am trying to run in a Jupyter notebook. The code sippet looks like this from sklearn.gaussian_process import GaussianProcess # define

Solution 1:

The error has the answer.

At yfit, MSE = gp.predict(xfit[:, np.newaxis]) you are trying to assign the result of predict to two variables while the predict only returns a single numpy.ndarray.

To solve this issue, run

yfit = gp.predict(xfit[:, np.newaxis])