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Iterative classification in relational databy: J. Neville, D. Jensen
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Notes for this articleThey present an iterative method that uses static relations to classify data. In subsequent iterations, classified data is used to infer dynamic relations that are further refined over subsequent iterations.
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AbstractRelational data offer a unique opportunity for improving the classification accuracy of statistical models. If two objects are related, inferring something about one object can aid inferences about the other. We present an iterative classification procedure that exploits this characteristic of relational data. This approach uses simple Bayesian classifiers in an iterative fashion, dynamically updating the attributes of some objects as inferences are made about related objects. Inferences made...
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