In the fourth section of the thesis , the method that constructing statistical features based - on time for connection records and using these features to construct classification models were studied in detail . in order to improve the accuracy of classification model and decrease the rate of false positive , some factors that may have bad influence on accuracy of classification model were analyzed and the method of selecting appropriate set of features was also provided 论文的第四部分，详细研究了使用网络连接记录的基本特征属性构建基于时间的统计特征属性方法，通过选择适当的特征属性集来提高异常检测模型的分类精度，降低误报率；同时分析了影响检测模型分类精度的因素；对不同实验条件下得到的实验结果进行了比较和分析。
In traditional decision - tree , the concepts and advantages and disadvantages of decision - tree are presented , and the application and research situation of decision - tree are analyzed . appling to web environment a web application used lazy decision - tree algorithm that comes from the idea of lazy based on model classificaton is developed 为了更好地满足网络环境下的应用需求，结合传统的决策树方法，基于“懒散的基于模型的分类”的思想，实现了一个网络环境下基于b / s模式的“懒散的决策树算法” 。
The problems mentioned above include the theory and method to divide the failure time prediction into three phases of long term , short term and imminent term , the method and principle to select and process parameters used by the failure time prediction , the step to establish the criterions of prediction , the principle to classify and select the prediction models . at the same time , a new method to deal with the results produced by different prediction models is pointed out 本文首先深入探讨了与滑坡时间预报精度密切相关的一些基本问题：滑坡预报的时间分段、监测资料选取与处理、预报判据确定、预报模型的分类及其选取原则：提出了多个模型预报结果的处理方法；然后详细论述了verhulst 、指数平滑法、卡尔曼虑波等具有代表性的滑坡预测预报模型的建模机理及其适用原则。
