关联规则算法在布鲁氏菌病危险因素分析中的应用

Application of Apriori Algorithm in the Analysis of Brucellosis

目的进行布鲁氏菌病相关危险因素研究,通过数据分析形成关联规则。方法采用关联规则算法(Apriori),对张北县养殖户2014—2015年的调查问卷资料进行分析,采用支持度和置信度作为衡量关联规则的强度。结果共形成30个强关联规则,这些强关联规则中蕴含着布病感染与性别、年龄、职业、从业年限、羊存栏量、羊购买地和戴手套情况等因素之间的关联关系。结论关联规则算法为评估布病危险因素提供了一套可借鉴的研究方法。

Objective The risk factors of brucellosis were studied, and association rules were formed through data mining. Methods The correlation rule Apriori algorithm was used to analyze the questionnaire data of Zhangbei farmers for 2014-2015 years, and the support degree and confidence degree were used to measure the intensity of the association rules. Results A total of 30 strong association rules were obtained. Those strong association rules contained the correlations between the infection of brucellosis and sex, age, occupation, years of employment, amount of sheep, purchase area and the condition of wearing gloves. Conclusion the correlation rule Apriori algorithm provides a reference method for evaluating the risk factors of brucellosis.