Discretization algorithm of continuous attributes in rough sets based on grey correlation degree
Xuegang Hu
Abstract
Xuegang Hu
Abstract
Discretization of continuous attributes is always one of the key problems that need urgent solutions in rough sets theory.Based on theory of grey system and rough sets,a new discretization algorithm of continuous attributes in decision table is offered.In this algorithm,the grey correlation degree of condition attributes for decision attribute is used to measure the importance of condition attributes;on the premise of keeping the stability of original decision table,all break points of every condition attributes are examined and the redundant ones are eliminated according to which the condition attributes are sorted in a descending order,and then the decision table is discretized.The time complexity of the algorithm is proposed and an example is investigated to verify its validity and practicability.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Discretization of continuous attributes is always one of the key problems that need urgent solutions in rough sets theory.Based on theory of grey system and rough sets,a new discretization algorithm of continuous attributes in decision table is offered.In this algorithm,the grey correlation degree of condition attributes for decision attribute is used to measure the importance of condition attributes;on the premise of keeping the stability of original decision table,all break points of every condition attributes are examined and the redundant ones are eliminated according to which the condition attributes are sorted in a descending order,and then the decision table is discretized.The time complexity of the algorithm is proposed and an example is investigated to verify its validity and practicability.
Key concepts: Rough set, Discretization of continuous features, Discretization, Degree (music), Decision table, Premise, Mathematics, Stability (learning theory)