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) $ ?

  • $\begingroup$ Do you know $M(f_i) \gt M(g_i), \forall i \in [1,n]$ or is $M(f_i) \gt M(g_i)$ only for a specific $i$? $\endgroup$ Nov 2 '20 at 5:15
  • $\begingroup$ All $i$ in this case $\endgroup$
    – yupbank
    Nov 15 '20 at 0:12

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