A hidden Markov model-based resignation prediction method and a related device. Said method comprises: constructing a pre-trained hidden Markov model on the basis of employee static information and influences of a working status on employee resignation intention, and training the pre-trained hidden Markov model by means of sample data of hired employees, so as to acquire a hidden Markov model for predicting a working status and a resignation probability of a job applicant (S101); acquiring application data of the job applicant, and constructing a static information feature data set of the job applicant on the basis of the application data (S102); and inputting the static information feature data set into the hidden Markov model, so as to predict the working status and the resignation probability of the job applicant after being hired (S103). In this way, the present invention provides reference information for a human resource management department to make the decision of whether to hire, avoiding recruiting, to a company, job applicants who are unstable and liable to resign, reducing the costs of human recruitment. In addition, the method has strong expandability on the time scale, for example, resignation warning, etc. can be achieved subsequently.
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