Heuristics for interesting class association rule mining a colorectal cancer database
作者：
Highlights：
• Heuristic operators are proposed for interesting class association rule mining.
• Our proposal remains focused and avoids the exponential curse of other alternatives.
• Generated rule sets are more attractive for the subsequent expert inspection.
• Interesting descriptions of certain colorectal cancer cases were obtained.
摘要
•Heuristic operators are proposed for interesting class association rule mining.•Our proposal remains focused and avoids the exponential curse of other alternatives.•Generated rule sets are more attractive for the subsequent expert inspection.•Interesting descriptions of certain colorectal cancer cases were obtained.
论文关键词：Interesting association rule mining,Class association rule mining,Heuristic operators,Colorectal cancer
论文评审过程：Received 15 November 2019, Revised 13 January 2020, Accepted 13 January 2020, Available online 25 January 2020, Version of Record 25 January 2020.
论文官网地址：https://doi.org/10.1016/j.ipm.2020.102207
