If we summarize what we've done so far in the "Addressing the problem of overfitting" article series, we've discussed three different techniques that can be used to mitigate overfitting. As you already know, Cross-validation (discussed in Part 1), Regularization (discussed in Part 2) and Dimensionality Reduction (discussed in Part 3) can effectively mitigate overfitting. In Part 4, today we discuss another useful technique called Creating Ensembles. However, this technique is limited to tree-based models. Someone can attempt to build a decision tree model (Step 1) without limiting the tree growth (without early stopping or without doing any hyperparameter tuning).