Abstract: Healthcare databases typically contain numerous attributes,and have both continuous and discrete type of attributes in hybrid data,which limits the mining efficiency of knowledge discovery on healthcare data to a great extent.Based on fuzzy rough sets theory,we studied the classification rule mining methods on hybrid data.By introducing the generalization thresholds for rule induction algorithm,the proposed method can reduce the size of extracted rule set and complexity of rules,which may improve the classification efficiency of rough sets based knowledge discovery method on healthcare data.Finally we conducted comparative experiments on medical decision tables to verify the effectiveness of mined rules of proposed algorithm.

Key words: E-health,Knowledge discovery,Rough sets theory,Rule induction,Hybrid data