The two main downsides to decision trees are that they often don't work well with large datasets, and they are highly susceptible to model overfitting. When tackling a binary classification problem, ...

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...

A decision tree is a flow chart created by a computer algorithm to make decisions or numeric predictions based on information in a digital data set. Decision trees can be used for both classification ...