An example shows this algorithm can achieve the minimal relative reduction of incomplete decision table.
通过实例说明，该算法能得到不完备决策表的最小相对约简。
Missing data filling and rules extraction in incomplete decision table are two important data mining problems.
不完全信息系统中遗失数据的补充和规则的提取，一直是数据挖掘技术面临的重要问题。
To obtain knowledge and data from incomplete decision table(IDT), the paper presents a new doubly variable precision limited tolerance rough set theory model(VPLTRST).
为了能够从不完备决策表（IDT）中进行知识发现和数据挖掘，提出一种新的具有对称性的双重可变精度限制容差关系粗集模型（VPLTRST）。
For a given incomplete decision table, the algorithm constructs decision tree using the improved ID3 algorithm, and fills the missing data in the process of constructing the decision tree.
对于给定的不完全决策表，该算法应用改进的ID 3算法来构造决策树，在构造决策树的过程中对遗失值进行补充。
How to find decision rules directly from such an incomplete information decision table is also discussed.
对如何直接从这种不完备信息表上找决策规则的方法也进行了讨论。
Rough set theory is a mathematical tool to deal with incomplete and uncertain knowledge, it can reduce knowledge under maintained the same classification ability of decision table.
粗糙集理论是一种处理不完整性和不确定性知识的数学工具，能够在保持决策表分类能力不变的情况下，进行知识的约简。
Rough set theory is a mathematical tool to deal with incomplete and uncertain knowledge, it can reduce knowledge under maintained the same classification ability of decision table.
粗糙集理论是一种处理不完整性和不确定性知识的数学工具，能够在保持决策表分类能力不变的情况下，进行知识的约简。
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