Decision tree analysis is a method of constructing a decision tree, which is a detailed representation of numerous potential solutions that can be utilized to address a specific problem to choose the ...

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, ...

Junior faculty are often told to protect their time, but nobody provides instructions for how to do so. As an assistant professor at a public university, I have struggled to balance my course load, my ...

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

Don’t know your convolutional neural networks from your boosted decision trees? Symmetry is here to help. It’s time for some deep learning. Check out this list to pick up some new terminology—and ...