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讨论数据挖掘问题 ,即从原始数据中构造决策规则。重点考虑不一致情况下的规则知识获取问题 ,即从包含不一致信息的数据中获取得到缺省规则 ,并研究在不一致条件下的决策规则选择策略 ,使之能够在不完全、不一致的条件下进行推理。同时将在 Skowron缺省规则获取算法的基础上 ,根据对不一致性的分析 ,提出从包含不一致信息的决策表中获取缺省规则 ,并能够对任意待识样本进行处理的方法。
Discuss data mining, that is, construct decision rules from raw data. The problem of rule knowledge acquisition under the condition of inconsistency is mainly considered, ie, the default rules are obtained from the data containing inconsistent information and the strategy of decision rules selection under inconsistent conditions is studied so that it can be reasoned under incomplete and inconsistent conditions . Based on the Skowron default rules acquisition algorithm, based on the analysis of inconsistency, a method of obtaining default rules from the decision table containing inconsistent information and processing any unknown samples is proposed.