| 1. | On decision tree complexity of boolean function and yao ' s question
布尔函数的判定树复杂性及问题 |
| 2. | Using algorithms of decision - tree , we can analyze customer loss , customer value , sales promotion and other modules , for the purpose of assistant decision - making
作者使用分类决策树归纳算法构建决策判定树，对客户流失、客户价值度、促销等模块进行分析，达到辅助决策的目的。 |
| 3. | The often - used classification is classification by decision tree induction , bayesian classification and bayesian belief networks , k - nearest neighbor classifiers , rough set theory and fuzzy set approaches
分类算法常见的有判定树归纳分类、贝叶斯分类和贝叶斯网络、 k -最临近分类、粗糙集方法以及模糊集方法。 |
| 4. | Judgment - tree method has been applied to solve lots of categorized problems successfully but so far in china it has never been applied into classification and prediction about customers " behavior of banks
判定树分类法已被成功地应用于许多分类问题，但应用于银行的客户行为分类预测研究在国内到目前为止还没有。 |
| 5. | Chapter two : given the data available and this data excavation task , it makes a study method comparison between neural network and judgment - tree . it confirms the latter as the model and presents a brief statement on judgment - tree
第二章：针对得到的实际数据和本次数据挖掘任务，通过与神经网络法的比较，确定判定树法为建模方法，同时对判定树原理进行简要论述。 |
| 6. | Bayesian classification is based on bayesian theorem . it can be comparable in interpretability with decision tree and in speed with neural network classifiers . bayesian classifiers have also exhibited high accuracy and speed when applied to large databases
该算法基于贝叶斯定理，可解释性方面可以与判定树相比，准确度可和神经网络分类算法相媲美，用于大型数据库时该算法已表现出高准确度与高速度。 |
| 7. | Chapter four : it explains and evaluates the established judgment - tree model . based on judgment result it points out how to give adoptable suggestions for banks to their different customers in adherence of this model . meanwhile it proposes an improved judgment - tree method
第四章：对建立的判定树模型进行评价和解释，根据模型结果就银行如何对不同客户进行差别管理提出建议，同时提出一种改进的判定树的方法。 |
| 8. | The purpose lies in the exploration of the method ' s technological problem in operating banks " data . and through the comparative analysis with the method of neural network , judgment - tree method excavates the potential characteristics of banks " customers and therefore it guides the management of customers " relation of banks
本文尝试采用判定树算法完成银行客户的分类预测，即通过建立判定树模型，找到银行中申请住房贷款客户潜在的人口学特征，然后根据不同特征的客户提出不同的管理方式，用于指导银行的客户关系管理。 |
| 9. | Chapter three : according to the basic principles of judgment - tree in data excavation , combing the concrete data of bank branches in middle china , it probes into setting up judgment - tree data model on the foundation of data pretreatment and concept division layer so as to predict customers in group and to test the model as well
第三章：使用中部某银行分行的具体数据，在数据预处理和概念分层的基础上用判定树法建立模型，对客户进行分类预测，找到不同客户的不同人口学特征。最后对判定树进行检验。 |
