Objective: To determine whether classification tree techniques used on survey data collected at enrollment from older adults in a Medicare HMO could predict the likelihood of an individual being in a ...

Binary Classification Using a scikit Decision Tree Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained model must be easily ...

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 ...

A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A multi-class classification problem is one where the goal is to predict the ...

Several approaches can be taken to predict case membership in the classes of a dependent variable. Classification and regression trees (CART) analysis has been cited repeatedly as a powerful ...

Now the buyside can monitor and rank its brokers’ algorithms and switching engines in real-time. Kissell Research Group now offers a measurement tool, dubbed Algorithmic Decision Selection Tree, which ...

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 ...