| 1. | Improves on the classification and regression trees technology , increases it ' s classification precision
对分类回归树数据挖掘技术进行了改进，使之具有更高的分类精度。 |
| 2. | The thesis combines generalized computing theory with classification and regression trees technology , makes the great theory innovation
本文把广义计算理论和数据挖掘技术相结合，具有很强的理论创新意义。 |
| 3. | Combines multi - rules neural network with classification and regression trees technology based on generalized computing theory , implements the abnormal customers recognition system
基于广义计算思想，把多准则神经网络和分类回归树技术相结合，实现异动客浙江大学硕士学位沦义缀户识别系统。 |
| 4. | Based on the generalized computing theory , the thesis combines multi - rules neural network with a kind of decision tree - classification and regression trees . further more , we put forward a new kind of abnormal customers recognition model
为进行客户关系管理，本文基于广义计算思想，将多准则神经网络和一种决策树? ?分类回归树相结合，提出了一种新的异动客户识别模型。 |
| 5. | The model can improve classification precision and recognition efficiency effectively , make full use of the advantages of multi - rules neural network and classification and regression trees , and make up their respective disadvantages at a certain extent
该模型能够有效提高分类精度和识别效率，充分利用多准则神经网络和分类回归树各自的优点，一定程度上避免各自的缺陷。 |
| 6. | And then , the thesis brings forward a new modeling method - abnormal customers recognition system based on generalized computing and classification and regression trees . the system is composed of multi - rules neural network learning part and classification and regression trees processing part
然后，通过深入研究多准则神经网络和决策树的特点，论文提出了将多准则神经网络应用于决策树的建模方法? ?基于多准则神经网络和分类回归树的异动客户识别系统。 |
| 7. | The work that is carried out by me for this project as follows : at first , works over the decision tree technology and the multi - rules neural network theory based on the generalized computing , outlines the advantages and disadvantages of the two theories , analyzes the possibility to combine multi - rules neural network with classification and regression trees , and studies some achievement in this field
为完成这个项目，本人所做的工作具体如下：首先研究了数据挖掘技术中的决策树技术和基于广义计算的多准则神经网络理论以及两种理论的优缺点。分析了多准则神经网络和决策树相结合的可能性及优势，并深入了解目前该方向的发展情况。 |
| 8. | Along with the rapid development of the technology of data warehouse and data mining , customer relationship management ( crm ) becomes more and more important . on this need , we advanced the project of abnormal customers recognition system based on generalized computing and classification and regression trees ( cart )
基于广义计算和分类回归树异动客户识别系统这个项目，是在数据仓库技术和数据挖掘技术迅速发展的基础上，针对企业客户关系管理的迫切需要而提出的。 |
| 9. | Classification and regression trees processing part introduces growing algorithm of cart , pruning algorithm of cart and selecting best tree algorithm etc . on the basis of the concerned new model , the thesis presents in details the designing of multi - rules neural network based cart system for abnormal customers recognition
在分类回归树部分，介绍了分类回归树的生长算法、最小代价?复杂性剪枝算法以及最优树选择等算法。提出了系统设计之后，论文详细介绍了该系统的开发，用以解决异动客户的识别问题。 |
