code: def predict(self, X):
          
          if np.random.random() < self.POU:
              # choose params at random to avoid local minima
              return Uniform(self.tunables).predict(X)
  
          return super(GPEiVelocity, self).predict(X)
docs: Use the POU value we computed in fit to choose randomly between GPEi and
          uniform random selection.