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| What is Multiple Classification Ripple Down Rule (MCRDR)? |
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| 1. Inferences |
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| The RDR inference operation is based on searching the KB represented as a decision list with each decision possibly refined again by another decision list. Once a rule is satisfied no rules below it are evaluated. In contrast MCRDR evaluates all the rules in the first level of the KB. It then evaluates the rules at the next level of refinement for each rule that was satisfied at the top level and so on. The process stops when there are no more children to evaluate or when none of these rules can be satisfied by the case in hand. It thus ends up with multiple paths, with each path representing a particular refinement sequence and hence multiple conclusions.
The structure of an MCRDR knowledge base can be drawn as an n-ary tree with each node representing a rule. Figure 1 shows such a structure and also shows the inference for a particular case. The inference process can be understood in terms of capturing ¡®paths¡¯, as shown below in Figure 1. When paths are produced there are a number of questions about whether the path produces a classification, whether the classification is redundant because it is produced elsewhere etc.
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Figure 1. MCRDR Process Model |
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