Evolutionary algorithms have emerged as a robust alternative to traditional greedy approaches for decision tree induction. By mimicking the natural selection process, these algorithms iterate over a ...

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 ...

Dr. James McCaffrey of Microsoft Research says the technique is easy to tune, works well with small datasets and produces highly interpretable predictions, but there are also trade-off cons. The goal ...

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 ...

David Kindness is a Certified Public Accountant (CPA) and an expert in the fields of financial accounting, corporate and individual tax planning and preparation, and investing and retirement planning.

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 graphic models of possible decisions and all ...

The visual data mining process, seen in the first part of this two-part article, revealed patterns in four dimensions between cumulative gas well production and independent variables. "Jump ...