In Machine learning, ensembling is taking multiple models and combining their predictions into a single prediction with better accuracy.
There are different ways of doing this.
The simplest one is averaging. This can be used for regression tasks.
Let’s say you have two models. The prediction of the first model is $P_1$ and the prediction of the second model is $P_2$. Then the prediction of their ensemble can be $\frac{P_1 + P_2}{2}$.
@article{yaltirakli, title = "Ensembling", author = "Yaltirakli, Gokberk", journal = "gkbrk.com", year = "2025", url = "https://www.gkbrk.com/ensembling" }
Gokberk Yaltirakli, "Ensembling", July, 2025. [Online]. Available: https://www.gkbrk.com/ensembling. [Accessed Jul. 23, 2025].
Yaltirakli, G. (2025, July 23). Ensembling. https://www.gkbrk.com/ensembling
Gokberk Yaltirakli, Ensembling, GKBRK.COM (Jul. 23, 2025), https://www.gkbrk.com/ensembling
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