Correlation of Attributes Based on Information Measure in DIS and Its Application to Attribute Reduction

The condition information measure of a decision attributes set w.r. t. to a condition attributes set is defined in a DIS. Based on the condition information measure the correlation of two condition attributes subsets w.r.t. a decision attributes set, the properties of correlation are discussed, and some concepts about DIS, such as necessary attribute, consistent attribute and attributes nuclear, etc, are described by using the correlation coefficient. By using the correlation of attributes a reduction algorithm is proposed, and an example is given to illustrate the algorithm is effective.

[1]  Wang Guo,et al.  Decision Table Reduction based on Conditional Information Entropy , 2002 .

[2]  Bao Qing Hu,et al.  Attribute reduction in ordered decision tables via evidence theory , 2016, Inf. Sci..

[3]  Yiyu Yao,et al.  Current research and future perspectives on decision-theoretic rough sets , 2015 .

[4]  Qinghua Hu,et al.  Rank Entropy-Based Decision Trees for Monotonic Classification , 2012, IEEE Transactions on Knowledge and Data Engineering.

[5]  Jiye Liang,et al.  Information granules and entropy theory in information systems , 2008, Science in China Series F: Information Sciences.

[6]  Qian Yu-hua Decision table reduction based on information entropy , 2005 .

[7]  Z. Jia-lu Rough Set Model Based on Random Fuzzy Sets , 2005 .

[8]  Bao Qing Hu,et al.  Approximate distribution reducts in inconsistent interval-valued ordered decision tables , 2014, Inf. Sci..

[9]  Miao Duo,et al.  An Information Representation of the Concepts and Operations in Rough Set Theory , 1999 .

[10]  Jialu Zhang,et al.  Rough set models based on random fuzzy sets and belief function of fuzzy sets , 2012, Int. J. Gen. Syst..

[11]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[12]  Xiaoling Liu,et al.  Fuzzy belief measure in random fuzzy information systems and its application to knowledge reduction , 2012, Neural Computing and Applications.

[13]  Miao Duo,et al.  A HEURISTIC ALGORITHM FOR REDUCTION OF KNOWLEDGE , 1999 .