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Learning classifier system, learning classifier generation method and program

机译:学习分类器系统,学习分类器生成方法和程序

摘要

PROBLEM TO BE SOLVED: To optimize a classifier when series data is classified by the classifier.SOLUTION: A learning classifier system obtains a collation set selected from a classifier that a classifier storage section has stored based on input series data, obtains an action set based on the value of an action section of the classifier in the collation set, updates the fitness value of the classifier in the action set by learning to subsume it when a plurality of classifiers in the action set can be subsumed into a single classifier, and selects or modifies the subsumed classifier based on a certain condition. In addition, the system reduces a condition section that the classifier owns to make the reduced classifier update the classifier stored by the storage section, and further, when an appropriate classifier is not available, creates a new classifier and store it in the storage section.SELECTED DRAWING: Figure 1
机译:解决的问题:要在分类器对序列数据进行分类时优化分类器解决方案:学习分类器系统从输入的序列数据中获取从分类器存储部分已存储的分类器中选择的排序规则集,并基于根据整理集中分类器的动作部分的值,通过学习将动作集中的分类器的多个分类器归为一个分类器来更新该分类器的适应度值,并选择或根据特定条件修改包含的分类器。另外,系统减少分类器所拥有的条件部分,以使简化的分类器更新由存储部分存储的分类器,并且,当没有合适的分类器时,创建新的分类器并将其存储在存储部分中。选定的图纸:图1

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