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GENERATING ACCURATE REASON CODES WITH COMPLEX NON-LINEAR MODELING AND NEURAL NETWORKS
GENERATING ACCURATE REASON CODES WITH COMPLEX NON-LINEAR MODELING AND NEURAL NETWORKS
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机译:利用复杂的非线性建模和神经网络生成精确的原因码
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摘要
A computer system computes a score for a received data exchange and, in accordance with a neural network and input variables determined by received current exchange and history data, the computed score indicates a condition suitable for a denial. A set of attribution scores are computed using an Alternating Decision Tree model in response to a computed score that is greater than a predetermined score threshold value for the denial. The computed score is provided to an assessment unit and, if the computed score indicates a condition suitable for the denial and if attribution scores are computed, then a predetermined number of input variable categories from a rank-ordered list of input variable categories is also provided to the assessment unit of the computer system.
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