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 ...

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 ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

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 ...

This is a preview. Log in through your library . Abstract Objective: Classification tree analysis is a potentially powerful tool for investigating multilevel interactions. Within the context of colon ...

The cotton bollworm, Helicoverpa armigera (Hϋbner) is one of the most important pests affecting crop production globally. The data-mining technique, for predicting pest incidence using biotic and ...

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 ...