利用数据挖掘技术对公交乘客特征状况的分析

分类在数据挖掘中是一项非常重要的任务.分类的目的是学会一个分类函数或分类模型,该模型能把数据库中的数据项映射到给定类别中的某一个,从而用于数据分类或预测.决策树是归纳学习和数据挖掘的重要方法,通常用来形成分类器和预测模型.主要研究了数据挖掘中的一种基于决策树的分类算法,以及在公交系统数据预测中的应用.在此基础上进一步讨论了ID3算法存在的一些问题并给出了解决方案和实现过程.其研究结果对开发交通规划决策支持系统具有重要的参考价值.

Estimation of transit passenger status with data mining

C1assification is one of the most important tasks of data mining.The goal of classification is to learn a classifying model which is used for prediction.Decision tree is an important method in induction learning as well as in data mining,which is used to form classification and predictive model.The categorized algorithm based on decision-tree algorithm is studied,and this kind of categorized algorithm to data prediction is applyed in transit system.And the classifying methods is studied,the detail implementation of one clas-sification method is given out:decision-tree algorithm.The study results of the paper have a very important referential value to develop decision support system of transportation planning.