gp.predict(test_X, point=MAP, diag=True)
I have implemented the rbf regression (squared-exponential kernel) using PyMC3 GP module. I want to estimate the error (uncertainty) of the predictions for each prediction. The predict function is expected to provide mean vector and the covariance matrix (or diagonal of the covariance matrix) of the predictive densities as the outputs.
I observed that the covariance is always in [0, 1].
- Why can’t it be more than 1?
- How do we interpret the uncertainty of predictions using the covariance?