Research And Implementation Of Enterprise Sales Staff Recruitment Model Based On Decision Tree

In the wake of computer technology developing,people's lives become more and more convenient,and the work efficiency is improved.At the same time,more and more data are stored in all walks of life.Data mining is the process of discovering knowledge from a large number of noisy data,and then discovering the knowledge from them.Data mining is a combination of a variety of disciplines,including data storage vector database technology,data statistical analysis,machine learning,neural networks,etc..This paper illustrates the importance of talent to the constant development of the enterprise,and then introduces the sales oriented enterprises have a high demand for sales personnel,but in the recruitment process,applicants themselves are often not in a very short period of time and shows its advantages and disadvantages;the personnel department due to time or limited capacity etc.the reason of the candidate's judgment may exist certain deviation,which give the applicant and the enterprise has hampered in the recruitment process.At the same time of storing a large number of sales of basic attribute information not used effectively,so we decided to use the data mining technology,using existing enterprise sales data for screening sales positions of the company's human resources in the candidates.Then it introduces the classification methods of data mining in detail,including decision tree classification,naive Bias classification and neural network classification.And illustrates the principle of decision tree classification method in CART algorithm,ID3 algorithm,C4.5 algorithm and several methods for decision tree pruning,and finally to the relevant data of the compass Limited by Share Ltd A sales staff as the basis,after screening pretreatment and attribute data,the use of R language CART algorithm and C4.5 algorithm is applied to the sample in data analysis,decision tree generation model.In the CART algorithm,the decision tree is pruned according to the complexity of the nodes,so as to optimize the model and try to avoid the over fitting of the data.Finally,the accuracy of the CART model and the C4.5 algorithm model are compared,and the model is applied to the sales staff screening system by using the C4.5 model.At the end of this paper,the author makes a summary and prospect of the research,and points out the shortcomings of the model and the improved methods.