Many scientific problems entail labeling data items with one of a given, finite set of classes based on features of the data items. For example, oncologists classify tumors as different known cancer ...

Decision trees are a simple but powerful prediction method. Figure 1: A classification decision tree is built by partitioning the predictor variable to reduce class mixing at each split. Figure 2: ...

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: 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 binary classification problem is one where the goal is to predict the value ...

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 ...