客戶流失分析外文翻譯-全文預(yù)覽
【正文】 ssion has been used in variety of areas, for example in childhood ADHD context [19], logistic regression has also been used in customer analysis. For example Buckinx et al. have used logistic regression for predicting partially defect customers in retail setting [4]. Multinomial regression has been used for predicting the customer’s future profitability, based on his demographic information and buying history in the book club [1]. In the logistic regression there can be only one dependent variable. Logistic regression applies imum likelihood estimation after transforming the dependent into a logistic variable [8]. Unlike the normal regression model the dependent variable in logistic regression is usually dichotomous: the dependent variable can take value 1 with probability q and value 0 with probability 1q. The logistic regression is presented here as it is presented on the book by . Cramer [8]. The logistic regression model has history in biological science sector. The normal regression model may be briefly revived by specifying. PX)?X ,Where X x1, x2,xn Which is the linear probability modelIt leads to the solution estimation by linear regression methods. In order to restrict the PX to the observed values of 0 and 1, plex properties must be attributed to the disturbanceε. If we wish to hold the probability PX between the bound 0 and 1 and to vary monotonically with X, we have to use other functions than linear functions. One of these functions that meet the requirements is logistic function, that is The results of the continuous probabilities that are produced by the logistic regression model will be discriminated into two groups by using a threshold value. Usually this threshold value is , and in this paper the threshold value will separate the churners from nonchurners. . Lift Curve In this paper we use binary prediction, ‘churn’ and ‘no churn’. We will analyze the estimation results of the logistic regression by using lift curve. The lift curve is related to the ROC curve of signal detection theory and precisionrecall curve in the information retrieval literature [16]. The lift is a measure of a predictive model calculated as the ratio between the results obtained with and without the predictive model. The Figure 1 shows a lift curve indicating perfect separation of types ‘churn’ and ‘no churn’: all churning customers are detected by the prediction model. The figure also represents a situation where no separation between customers has been done. This type of situation occurs when the churn probabilities are random. Figure 1 Lift curve for indicating perfect discrimination and no discrimination of churners and nonchurners. The lift curve will help to analyze the amount of true churners are discriminated in each subset. This will be extremely helpful in a marketing situation where a group of customers are to be contacted. Thus a pany can count how many customers to contact if an example of 25 % of potential churners is to be contacted. Or if the marketing effort has a limit of 5 000 customer contacts, how many churners are then reached. 出處 :Teemu Mutanen. Customer churn analysis ? a case study: Independent Research Project in Applied Mathematics [R].10 March 2020 二、翻譯文章 標(biāo)題 :客戶流失分析 個案研究 譯文 : 客戶流失分析 個案研究 Teemu Mutanen 摘要 客戶價值分析是一個好的市場營銷和客戶關(guān)系管理戰(zhàn)略的關(guān)鍵。這項研究的目的是運用 logistic回歸方法來預(yù)測客戶流失和通過個人零售銀行業(yè)務(wù)的公司數(shù)據(jù)來分析客戶流失和非流失。
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