40 Algorithms Every Programmer Should Know

Weaknesses

The following are the weaknesses of decision tree classifiers:

• If the tree generated by the decision tree classifier goes too deep, the rules capture too many details, resulting in an overfitted model. While using a decision tree algorithm, we need to be aware that decision trees are vulnerable to overfitting and so we need to prune the tree, whenever necessary, to prevent this.

• A weakness of decision tree classifiers is their inability to capture non-linear relationships in the rules that they create.