If Bagging Already Uses 100 Trees, Why Was Random Forest Invented?

After finally understanding Bagging, I thought I was done with ensemble learning. The idea made sense. Take multiple bootstrap samples. Train multiple Decision Trees. Combine their predictions using majority voting. Variance decreases. Simple. Then I came across another algorithm: Random Forest. My first reaction was honest: "Wait... isn't this just Bagging with a fancy name?" It turns out the answer is no . And the reason is surprisingly interesting. Bagging Solves One Problem Bagging makes…