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 ...

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 ...

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 ...

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 ...

Objective: This study developed and tested a computer method to automatically assign subjects to aggregate work groups based on their free text work descriptions. Methods: The Double Root Extended ...

Dermatologists typically classify skin lesions based on multiple data sources. Algorithms that fuse the information together can support this classification. An international research team has now ...

Machine learning (ML) opens new opportunities for advancing the classification of traumatic brain injury (TBI). Effectively classifying TBI cases remains a challenge due to the complexity of cognitive ...