In this paper we propose a method of extracting rules in Incomplete Information System based on an irregular decision table. Need not to make estimation of missing attribute value, we get the rule set contains no missing attribute value. The experiment justify, the accuracy of obtained rule set is almost same with the highest accuracy among those of the estimating missing attribute value methods. ? 2003 Published by Elsevier Science B.V.EI
In a previous paper three types of missing attribute values: lost values, attribute-concept values a...
Rough sets theory is now becoming a mathematical foundation of soft computing. This theory makes use...
The key point of the tolerance relation or similarity relation presented in the literature is to ass...
AbstractIn this paper we propose a method of extracting rules in Incomplete Information System based...
In this paper, a new extracting rule algorithm from incomplete information system is proposed. First...
Almost algorithms based on the rough sets, such as mean value method, maximum frequency method, mode...
A novel interval set approach is proposed in this paper to induce classification rules from incomple...
AbstractA novel interval set approach is proposed in this paper to induce classification rules from ...
The problem of knowledge discovering in the form of rules from databases with incomplete information...
AbstractThis paper deals with knowledge discovering in incomplete information systems (IIS).By an II...
In this paper we assume that a data set is presented in the form of the incompletely specified decis...
Abstract. In this paper we present a new approach to handling in-complete information and classifier...
Analyzes the traditional methods of extracting decision rules in Rough Sets, defines the concept of ...
In the majority of papers on rough set theory itis assumed that the information is complete, i.e., t...
The rough set theory, based on the original definition of the indiscernibility relation, is not usef...
In a previous paper three types of missing attribute values: lost values, attribute-concept values a...
Rough sets theory is now becoming a mathematical foundation of soft computing. This theory makes use...
The key point of the tolerance relation or similarity relation presented in the literature is to ass...
AbstractIn this paper we propose a method of extracting rules in Incomplete Information System based...
In this paper, a new extracting rule algorithm from incomplete information system is proposed. First...
Almost algorithms based on the rough sets, such as mean value method, maximum frequency method, mode...
A novel interval set approach is proposed in this paper to induce classification rules from incomple...
AbstractA novel interval set approach is proposed in this paper to induce classification rules from ...
The problem of knowledge discovering in the form of rules from databases with incomplete information...
AbstractThis paper deals with knowledge discovering in incomplete information systems (IIS).By an II...
In this paper we assume that a data set is presented in the form of the incompletely specified decis...
Abstract. In this paper we present a new approach to handling in-complete information and classifier...
Analyzes the traditional methods of extracting decision rules in Rough Sets, defines the concept of ...
In the majority of papers on rough set theory itis assumed that the information is complete, i.e., t...
The rough set theory, based on the original definition of the indiscernibility relation, is not usef...
In a previous paper three types of missing attribute values: lost values, attribute-concept values a...
Rough sets theory is now becoming a mathematical foundation of soft computing. This theory makes use...
The key point of the tolerance relation or similarity relation presented in the literature is to ass...