CAJ | 학술논문

处理连续属性离散化是决策树分类方法中C5.0算法在创建决策树时对数据表示空间的简化的一个重要问题,采用合理有效的连续属性离散化方法可以提高创建决策树的分类预测精度.在分析C5.0算法的离散化方法的不足之处后,提出一种改进Chi2算法的方法,能更合理更准确地对连续属性进行离散化,在此基础上创建的决策树具有更好的准确率.实验结果表明,基于改进方法的C5.0算法创建的决策树分类模型具有较高的分类准确率.
처리련속속성리산화시결책수분류방법중C5.0산법재창건결책수시대수거표시공간적간화적일개중요문제,채용합리유효적련속속성리산화방법가이제고창건결책수적분류예측정도.재분석C5.0산법적리산화방법적불족지처후,제출일충개진Chi2산법적방법,능경합리경준학지대련속속성진행리산화,재차기출상창건적결책수구유경호적준학솔.실험결과표명,기우개진방법적C5.0산법창건적결책수분류모형구유교고적분류준학솔.
How to discretize continuous attributes is an important problem that simplifies the representation of data set when building a decision tree based on C5.0 algorithm. Adopting a more effective and sound method ofdiscretization can heighten the predictive accuracy of decision tree. To do this, improved method of Chi2 algorithm is presented after studying the C5.0 algorithm and Chi2 algorithm and analyzing their drawbacks of discretization, which discretizes the renl value attributes exactly and reasonably while growing an accurate decision-tree. The experiment results show the validity of the proposed method.