(self)
return incumbent, incumbent_value
Returns the best observed point and its function value

        Returns
        ----------
        incumbent: ndarray (D,)
            current incumbent
        incumbent_value: ndarray (N,)
            the observed value of the incumbent
Returns the best observed point and its function value
Returns the best observed point and its function value
def get_incumbent(self):
        """
        Returns the best observed point and its function value

        Returns
        ----------
        incumbent: ndarray (D,)
            current incumbent
        incumbent_value: ndarray (N,)
            the observed value of the incumbent
        """

        projection = np.ones([self.original_X.shape[0], 1]) * 1

        X_projected = np.concatenate((self.original_X[:, :-1], projection), axis=1)
        X_norm = normalize(X_projected, self.lower, self.upper)

        m, _ = self.predict(X_norm)

        best = np.argmin(m)
        incumbent = X_projected[best]
        incumbent_value = m[best]

        return incumbent, incumbent_value
def get_incumbent ( self ) : projection = np . ones ( [ self . original_X . shape [ 0 ] , 1 ] ) * 1 X_projected = np . concatenate ( ( self . original_X [ : , : - 1 ] , projection ) , axis = 1 ) X_norm = normalize ( X_projected , self . lower , self . upper ) m , _ = self . predict ( X_norm ) best = np . argmin ( m ) incumbent = X_projected [ best ] incumbent_value = m [ best ] return incumbent , incumbent_value