I’m working on a machine learning project, and my dataset contains variables about social, demographic and economic aspects of 218 countries, ranging from 1960 to 2022. The target variable is a binary variable (Yes or No) that represents if the country has had at least one attempt of coup d’etat in a specific year.
My question is: what are the best classification models for multi-level data?
From consulting different sources, I’ve wrote down these models (no particular order):
- Random Forest
- XGBoost
- Logistic Classification
- Decision Tree
Are they the wrong ones? Are there more models I’m not aware of?
If not, do you know any source I can use to implement these models in R?
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