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An enhanced Customer Relationship Management classification framework with Partial Focus Feature Reduction

机译:增强的客户关系管理分类框架,减少了部分关注的功能

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摘要

Effective data mining solutions have for long been anticipated in Customer Relationship Management (CRM) to accurately predict customer behavior, but from various industry research and case studies we have observed sub-optimal CRM classification models due to inferior data quality inherent to CRM data set. In this paper, one type of CRM data with a distinctive distribution pattern of Reduced Dimensionality is discussed. A new classification framework termed Partial Focus Feature Reduction is proposed to resolve CRM data set with Reduced Dimensionality using a collection of efficient data mining techniques characterizing a specially tailored modality grouping method to significantly improve data quality and feature relevancy after preprocessing, eventually achieving excellent classification performance with the right combination of classification algorithms.
机译:在客户关系管理(CRM)中长期以来一直期望有有效的数据挖掘解决方案来准确预测客户行为,但是由于CRM数据集固有的数据质量较差,因此在各种行业研究和案例研究中,我们观察到了次优的CRM分类模型。在本文中,讨论了一种具有减少维数的独特分布模式的CRM数据类型。提出了一种新的分类框架,称为“部分关注特征减少”,以使用一组有效的数据挖掘技术来解析具有降维特征的CRM数据集,这些数据挖掘技术表征了一种专门定制的模态分组方法,可显着提高预处理后的数据质量和特征相关性,最终实现出色的分类性能与分类算法的正确组合。

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