基于Boosting的市场值函数算法及其评价

发现具有潜在市场价值的客户群是直销中的一个关键问题，尽管一些标准的数据挖掘算法可以用来解决此问题，但效果并不理想．为此，采用市场值函数算法，它以信息论为基础，通过构造一个线性市场值函数来对客户进行排序，从而发现最具有潜在市场价值的客户群．实验结果表明，它的评价值可达80％以上，并且具有很好的可解释性．同时，将Boosting算法应用到市场值函数算法中，用以提高市场值函数的预测效果；在3个不同的数据集上进行了实验，评价值均提高了一个百分点．

Market Value Algorithm Based on Boosting and Its Evaluation

entification of customers with potential market value is a key problem in direct marketing. Although some standard data mining methods may be applied for the purpose of direct marketing, no ideal results have been achieved. Therefore, based on the informational theory, the market value algorithm, is adopted to propose a linear market value function so as to discover the customers with the most potential market value. The experiment result shows that its evaluation value can be up to more than 80% and this algorithm is well interpretable. The authors try to improve the predictive ability of market value algorithm by applying Boosting to it Experiments are carried out on three different data sets and the result shows that one percent point of evaluation value can be improved on average.