C4.5: programs for machine learning
C4.5: programs for machine learning
Neural Networks
Machine Learning
Knowledge-based neurocomputing
Knowledge-based neurocomputing
IEEE Transactions on Pattern Analysis and Machine Intelligence
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Stability problems with artificial neural networks and the ensemble solution
Artificial Intelligence in Medicine
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This paper introduces a new method for explaining the predictions of ensembles of neural networks on a case by case basis. The approach of explaining individual examples differs from much of the current research which focuses on producing a global model of the phenomenon under investigation. Explaining individual results is accomplished by modelling each of the networks as a rule-set and computing the resulting coverage statistics for each rule given the data used to train the network. This coverage information is then used to choose the rule or rules that best describe the example under investigation. This approach is based on the premise that ensembles perform an implicit problem space decomposition with ensemble members specialising in different regions of the problem space. Thus explaining an ensemble involves explaining the ensemble members that best fit the example.