摘要
针对现有处理不完全数据的填充方法,对数据集引入新的噪声这一问题,提出一种基于最大间隔理论的预测模型,直接使用含缺失特征的样本进行预测,通过实验验证该模型优于常用的填充模型。
Aiming at the phenomenon that imputation methods to deal with incomplete data will introduce additional noise,this paper proposes a novel forecast model based on max-margin principle.This method directly uses data with absent features to predict,and experimental results show that compared with imputation methods,this model is more effective in the prediction accuracy.
出处
《计算机工程与应用》
CSCD
2012年第33期68-72,共5页
Computer Engineering and Applications
基金
国家重点基金(No.91118005)
重庆市自然科学基金(CSTC2010BB2217)
中央高校基本科研业务费面上项目(No.CDJRC10180009
No.CDJXS10182216)
关键词
最大间隔
不完全数据
软件可靠性
可靠性预测
max-margin principle
incomplete data
software reliability
reliability prediction