Grain Output Prediction based on Rough Set

被引：1

作者：

Li, Ju ^{[1
]}

Wang, Xing ^{[2
]}

Chen, Jie ^{[1
]}

机构：

[1] Chang Shu Inst Technol, Sch Engn & Comp Sci, Changshu 215500, Jiangsu, Peoples R China

[2] Nanjing Univ Informat Sci & Technol, Sch Comp Software, Nanjing 210044, Jiangsu, Peoples R China

来源：

2010 SYMPOSIUM ON SECURITY DETECTION AND INFORMATION PROCESSING | 2010年 / 7卷

关键词：

rough set; grain output prediction; feature selection; attribute importance;

D O I：

10.1016/j.proeng.2010.11.069

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Situation for causing the high of times and the low of accuracy of text categorization because of many food features, raised construction of China's grain output prediction model using feature selection rough set - based. Proved: construction of China's grain output prediction model using feature selection rough set - based, the method compared to the previous method can achieve the purpose of dimensionality reduction, and its predictive value is particularly realistic. (c) 2009 Published by Elsevier Ltd.

引用

页码：422 / 425

页数：4