Dynamics of modeling in data mining: interpretive approach to bankruptcy prediction
Journal of Management Information Systems - Special section: Data mining
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Models of consensus are used in the knowledge acquisition process to determine what knowledge is built into a system. Unfortunately, in some cases, the consensus position is incorrect. This paper develops two analytic models of consensus that can be useful in the knowledge acquisition process. Conditions are found to indicate when the consensus model should be used in knowledge acquisition. The second is a Bayesian model of the use of consensus judgment and knowledge acquisition. Conditions similar to those for the binomial model are found to be appropriate for determining when the probability of consensus is correct is greater than the probability that consensus is incorrect. Knowledge Acquisition, Consensus, Decision Support Systems, Machine Learning