Decision trees are major components of finance, philosophy, and decision analysis in university classes. Yet, many students ...

Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained model must be easily interpretable, but often don't work well with large ...

Here is a [recently developed] tool for analyzing the choices, risks, objectives, monetary gains, and information needs ...

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, ...