Department of Electrical Engineering and Computer Science University of Kansas Lawrence, KS 66045, USA;
Department of Electrical Engineering and Computer Science University of Kansas Lawrence, KS 66045, USA and Institute of Computer Science Polish Academy of Sciences 01-237 Warsaw, Poland;
data mining; rule induction; rough set theory; probabilistic approximations; parameterized approximations; incomplete data;
机译:来自不完整数据集的规则归纳的概率近似分析
机译:两种扩展到概率近似的MLEM2规则归纳算法的比较
机译:用于规则归纳的三个概率逼近的实验比较
机译:从缺少属性值的数据中对规则进行归纳的概率近似值有多好?
机译:规则诱导数据集与设定值属性
机译:缺失数据研究中平衡线性混合模型的多元测试功效逼近
机译:数据集属性值缺失规则的生成和验证的粗糙集方法