A decision tree analytical approach has been proposed, which incorporates quality of life outcomes and survival data to quantitatively determine the optimal approach for individual patients with ...

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 ...

This paper presents a general framework based on copulas for modeling dependent multivariate uncertainties through the use of a decision tree. The proposed dependent decision tree model allows ...

How to Evaluate a Decision Tree Model. A decision tree can help you make tough choices between different paths and outcomes, but only if you evaluate the model correctly. Decision trees are ...

Decision tree regression is a fundamental technique that can be used by itself, and is also the basis for powerful ensemble techniques (a collection of many decision trees), notably, AdaBoost ...

An international consortium including neuroscientists from UNIGE has published a complete map of the mouse brain activation ...

This paper, therefore, shows how one decision-tree model was used in a farming systems program at a national agricultural research center to provide specific recommendations to a technical team ...

Reviewed by David Kindness Fact checked by Vikki Velasquez Decision trees are major components of finance, philosophy, and decision analysis in university classes. Yet, many students and graduates ...