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A hybrid FAM–CART model and its application to medical data classification
journal contribution
posted on 2015-02-21, 00:00 authored by M Seera, Chee Peng LimChee Peng Lim, S C Tan, C K LooIn 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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Journal
Neural Computing and ApplicationsPublisher
Springer-VerlagPublisher DOI
ISSN
0941-0643Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2015, Springer VerlagUsage metrics
Keywords
Classification and regression treeDecision supportFuzzy ARTMAPPattern classificationRule extractionStability–plasticity dilemmaScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer ScienceStability-plasticity dilemmaARTIFICIAL NEURAL-NETWORKSDECISION-SUPPORT-SYSTEMSFEATURE-SELECTIONGENETIC ALGORITHMSDISEASE DIAGNOSISFAULT-DIAGNOSISVECTOR MACHINESHEART-DISEASETREE ANALYSISArtificial Intelligence and Image Processing
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