摘要缺失数据的处理是数据挖掘领域进行数据预处理的一个重要问题. 传统的缺失数据填补方法
大部分是基于概率分布等一些统计假设, 对于大数据集的数据挖掘不一定是最适合的方法 …

Incomplete data are questions without answers or variables without observations. Even a
small percentage of missing data can cause serious problems with the analysis leading to …

This paper discusses and proposes a rough set model for an incomplete information system,
which defines an extended tolerance relation using frequency of attribute values in such a …

Organizations aim at harnessing predictive insights, using the vast real-time data stores that
they have accumulated through the years, using data mining techniques. Health sector, has …

We describe probabilistic approximations dealing with missing values. A relation used by
Kryszkiewicz for indiscernibility of missing values is applied to deal with the missing values …

We check Kryszkiewicz's approach for rough sets in data tables containing missing values in
terms of Lipski's approach based on possible world semantics. The relation for …

This paper discusses some extension of Rough set approach in Incomplete decision tables
to deal with a problem of tolerance relation. Those approaches have been widely used to …

When extracting any information from a data table with incomplete information, following
Lipski we only know the lower and the upper bound of the information. Methods of rough …

The rough set theory, based on the original definition of complete information system, is not
useful for analyzing the incomplete information system where some values of attributes are …

The problem of classification has been studied by many authors, and different methods have
been developed. In this paper a combination of rough sets and fuzzy logic for classification …