By using rough set theory, this paper structures classification rules and processes the support vector machine feedback results with learning the train set.
利用粗糙集理论，通过对训练集的学习，构造分类规则，对支持向量机反馈后的结果再次进行处理。
As an effect tool of pattern recognition and data processing, rough set theory (RST) and support vector machine (SVM) have become the focus of research in machine learning.
粗糙集理论(rst)与支持向量机(SVM)作为模式识别，数据处理的有效工具，已成为机器学习的研究热点。
Relevance feedback algorithm based on support vector machine and rough set for image retrieval is approached.
研究基于支持向量机和粗糙集的相关反馈图像检索算法。
According to the border region of rough set theory and the merits of V-support vector machine, the algorithm of support vector clustering is improved.
根据粗糙集理论的边界区域和V -支持向量机的优点对支持向量聚类算法进行改进。
That using the reduction attributes of rough set reduced some redundant attributes, improved the real time of data processing by support vector machine, and shorten the time for training sample.
利用粗糙集的属性约简性来约简掉一些冗余属性，提高了支持向量机进行数据处理的实时性，缩短了训练样本的时间。
In addition, we combined SVM with rough set theory, and got rough support vector machine algorithm (RSVM).
此外，将支持向量机与粗糙集理论相结合，得到粗糙支持向量机算法(RSVM)。
And combining rough set and support vector machine, the mixture prediction model is established based on rough set and support vector machine.
将粗糙集与支持向量机两者结合，并建立了基于粗糙集——支持向量机的混合预测模型。
Using Intelligent prediction system which is constituted by rough set and support vector machine, this paper studies the low efficiency of project cost prediction.
本文采用粗糙集和支持向量机这些数学方法构成智能预测系统，研究解决工程造价预测效率不高这一难题。
Similarly, based on rough set theory to feature-set reduction, in the optimal decision based on the use of the property least squares support vector machine classifier to identify the flow pattern.
同样，基于粗糙集理论对特征集进行约简，在最优决策属性的基础上使用最小二乘支持向量机分类器对流型进行识别。
To combine the attribute reduction algorithm and the incremental training algorithm of support vector machine, a support vector machine classifier based on rough set is constructed.
将属性约简算法和支持向量机增量训练算法相结合，构造基于粗糙集数据预处理的支持向量机分类器。
To combine the attribute reduction algorithm and the incremental training algorithm of support vector machine, a support vector machine classifier based on rough set is constructed.
将属性约简算法和支持向量机增量训练算法相结合，构造基于粗糙集数据预处理的支持向量机分类器。
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