摘要
讨论了研究图像情感语义规则的意义,给出了粗糙集中重要概念的定义以及极小极大规则学习算法的描述。提出了将极小极大规则学习应用于图像情感语义规则简化的方法。首先使用粗糙集理论中的属性约简对训练集进行简化,再使用决策树算法得到规则集,最后将极小极大规则算法应用于决策树规则的简化。此方法缩小了简化的范围,并能保证图像情感语义规则的准确率,且可减少规则的总数量。
This article discussed the significance of studying the semantic rules of image emotion. It gave the concept of rough set and described the learning algorithm about minimal-and-maximal rules. The author put forward the method of simplifying the semantic rules in image emotion by using this learning algorithm. Firstly, used the attribute reduction of rough set to simplify the train set. Then,got the rule set by using the decision tree algorithm. Finally, applied the learning algorithm about minimal-and-maximal rules to simplify the decision tree algorithm. The advantage of this method is while reducing the total quantity of the rules, it can narrow the scope of simplification, and ensure the accuracy of the semantic rules in image emotion and reduce the total number of rules.
出处
《计算机科学》
CSCD
北大核心
2009年第10期240-243,共4页
Computer Science
基金
国家自然科学基金项目(60773004)
山西省自然科学基金(2006011030
2007011050)资助
关键词
图像情感
粗糙集
属性约简
规则简化
Image emotion, Rough set, Attribute reduction, Rule simplification