Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods

Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean).     

数学构造性方法的应用

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体育运动中神经-肌肉疲劳研究的新进展

简要回顾神经-肌肉疲劳的研究历史,并从生理学角度综述近年来国内外有关中枢性疲劳与外周疲劳的理论研究成果以及在实验研究方面取得的新进展.有关中枢性疲劳,着重介绍5-羟色胺、多巴胺、乙酰胆碱等中枢神经递质参与运动性疲劳的形成与恢复的新证据与新理论(可能的机制).有关外周疲劳机制,从神经肌肉接头处的超微结构到骨骼肌细胞的亚细胞结构等可能发生疲劳的部位,将近年来的研究成果作简要概括.这些研究成果表明有关运动性疲劳的生理学研究进入到亚细胞水平与分子水平.     

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体育产业是现代经济发展的新形式，是发达国家的经济之柱产业。本文从我国产业结构、我国城镇与农村收入和消费结构变动、我国加入WTO及我国将举办2008年北京奥运会等变动因素，对我国体育产业发展的影响因素进行了分析研究。     

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采用文献资料调研、专家及问卷调查和数理统计等方法对我国部分项目优秀教练员的能力结构进行研究,探讨从事不同运动项目的优秀教练员所具有的能力结构与共同特征.     

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文章通过对“with+复合结构”外延逻辑关系的分析,认为该结构的语篇意义在于能调动读者的成像、感应、直觉等心理机能,让读者深深体味到英语语言的魅力之所在。     

对我国部分项目优秀教练员能力结构的研究

以我国优秀教练员为对象,采用文献资料法、调查法和数理统计法对我国部分项目优秀教练员能力结构进行研究.探索从事不同运动项目的优秀教练员都具有怎样的能力结构,其间又有哪些共同特征,它们对优秀教练员的成长都起过什么样的作用等等.     

广西电大远程教育网络系统改造与应用设想

网络发展日新月异,网络上的新设备、新技术、新应用层出不穷,出现了许多新的组网方式。电大网络的数据量、用户量和访问量的迅速增大,对网络技术和网络平台提出了更高的要求。广西电大原有的组网方式太复杂,维护困难,运行成本高。因此,在体现其低资费、高效率和电大可持续发展的前提下,必须对电大网络进行重新构建。本文主要阐述全区电大网络改建和应用的初步设想。     

论竞技武术套路教练员的素质

通过对部分竞技武术套路教练员的调查分析，提出了套路教练员应该具备的思想素质和5种基本知识与能力。并阐述了各种素质之间的内在联系与区别，旨在提高武术套路教练员的个体素质。     

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太极拳是中华武术最具代表性的拳种之一,在世界范围内得到了广泛传播,其健身和技击的价值得到了广泛的认同,运用耗散结构理论阐述了太极拳的健身技击原理.