Suppose I have two fitted ensemble models $F_1 := (f_1, f_2, f_3, \cdots f_n)$ and $G_1 := (g_1, g_2, g_3, \cdots g_n)$.
And they were using the same ensemble methods (boosting or bagging).
And I am using some measurement for model performance $M: f_i \to \mathbb{R}^+$, higher the better.
And I know beforehand $M(f_i) \gt M(g_i), \forall i \in [1,n]$, can I conclude $M(F) \gt M(G) $ ?