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A hybrid FAM–CART model and its application to medical data classification

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Abstract

In this paper, a hybrid model consisting of the fuzzy ARTMAP (FAM) neural network and the classification and regression tree (CART) is formulated. FAM is useful for tackling the stability–plasticity dilemma pertaining to data-based learning systems, while CART is useful for depicting its learned knowledge explicitly in a tree structure. By combining the benefits of both models, FAM–CART is capable of learning data samples stably and, at the same time, explaining its predictions with a set of decision rules. In other words, FAM–CART possesses two important properties of an intelligent system, i.e., learning in a stable manner (by overcoming the stability–plasticity dilemma) and extracting useful explanatory rules (by overcoming the opaqueness issue). To evaluate the usefulness of FAM–CART, six benchmark medical data sets from the UCI repository of machine learning and a real-world medical data classification problem are used for evaluation. For performance comparison, a number of performance metrics which include accuracy, specificity, sensitivity, and the area under the receiver operation characteristic curve are computed. The results are quantified with statistical indicators and compared with those reported in the literature. The outcomes positively indicate that FAM–CART is effective for undertaking data classification tasks. In addition to producing good results, it provides justifications of the predictions in the form of a decision tree so that domain users can easily understand the predictions, therefore making it a useful decision support tool.

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Acknowledgments

This research is partially supported by University of Malaya Research Grant RP003D-13ICT.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia

    Manjeevan Seera & Chu Kiong Loo

  2. Centre for Intelligent Systems Research, Deakin University, Geelong, VIC, Australia

    Chee Peng Lim

  3. Faculty of Information Science and Technology, Multimedia University, Melaka, Malaysia

    Shing Chiang Tan

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  1. Manjeevan Seera
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  2. Chee Peng Lim
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  3. Shing Chiang Tan
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  4. Chu Kiong Loo
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Correspondence to Manjeevan Seera.

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Seera, M., Lim, C.P., Tan, S.C. et al. A hybrid FAM–CART model and its application to medical data classification. Neural Comput & Applic 26, 1799–1811 (2015). https://doi.org/10.1007/s00521-015-1852-9

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  • DOI: https://doi.org/10.1007/s00521-015-1852-9

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