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What are decision trees?

Nature Biotechnology volume 26, pages 1011–1013 (2008)Cite this article

Decision trees have been applied to problems such as assigning protein function and predicting splice sites. How do these classifiers work, what types of problems can they solve and what are their advantages over alternatives?

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 types using biopsies, patient records and other assays. Decision trees, such as C4.5 (ref. 1), CART2 and newer variants, are classifiers that predict class labels for data items. Decision trees are at their heart a fairly simple type of classifier, and this is one of their advantages.

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Figure 1: A hypothetical example of how a decision tree might predict protein-protein interactions.

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Authors and Affiliations

  1. Carl Kingsford and Steven L. Salzberg are in the Department of Computer Science, Institute for Advanced Computer Studies and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA. carlk@cs.umd.edu salzberg@umiacs.umd.edu,

    Carl Kingsford & Steven L Salzberg

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Kingsford, C., Salzberg, S. What are decision trees?. Nat Biotechnol 26, 1011–1013 (2008). https://doi.org/10.1038/nbt0908-1011

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