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Association Rule Mining to Identify Critical Demographic Variables Influencing the Degree of Burnout in A Regional Teaching Hospital
2017
This study uses apriori algorithm of IBM SPSS Modeler 14.1 on nine questions of emotional exhaustion dimension along with ten demographic variables from a regional teaching hospital in Taiwan in 2014 to identify critical demographic variables that influence the degree of burnout. By setting up the support of 25%, confidence of 80%, and lift of 1.5, twenty nine rules are found. To further refine the rules by their similarities, seven major combinations are summarized. The major characteristics
doi:10.18421/tem63-10
fatcat:6cnj4nteujdr5gk5hvnaep4ia4