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 data ...

The outcome percentages must total 100 for each set of possible outcomes for the same branch. For example, for a decision ... data for Excel... Look at the possible decisions on the tree for ...

Many scientific problems entail labeling data items with one ... is one of their advantages. Decision trees are constructed by analyzing a set of training examples for which the class labels ...

First, we build a reference tree on the entire data set and ... In our example, we did not differentially penalize the classifier for misclassifying specific classes. Decision trees are very ...

Decision trees are useful modeling tools to help you make decisions. Decision trees offer a structure to organize options and help you understand the possible results of choosing specific options.