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。
In the paper, we make a new inductive learning approach to knowledge representation system based on rough set theory.
本文基于粗集理论，针对知识表达系统提出了一种新的归纳学习方法。
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。
Starting from the learning needs of students, the course should be set as project management course of theory and practice integration, among that organic integration of knowledge is a key technology.
从学生学习需求出发，该课程应设定为理实一体化项目课程，其中知识的有机融入是一项关键技术。
Secondly, the writer brings forward a set of schemes feasible in theory and practice for the implementation of the inquiry-based learning method in the inquiry course.
其次，对探究性学习在研究性学习课程中的实施过程进行了探讨，提出了一套在理论上和实践上都较为可行的方案；
Support vector machine (SVM) based on the structural risk minimization of statistical learning theory is a method of machine learning for small sample set.
基于统计学习理论中结构风险最小化原则的支持向量机是易于小样本的机器学习方法。
Theory of situated cognition insist set up students-centered learning environment.
情境认知理论强调创设以学生为中心的学习环境。
Compared with other learning theories of the past, conceptual change theory seems to more cogently set forth the issue of learning mechanism.
观念转变理论与以往的学习理论相比，更为有效地解释了学习发生的机制问题。
Rough set theory is one of the main subjects in the field of machine learning and data mining.
粗糙集理论是机器学习和数据挖掘领域的重要课题之一，其中属性约简算法是该理论实现应用的主要算法。
According to the theory of learning. Of enquiry and related history education theory, we have set four models of high school history teaching.
根据研究性学习理论和相关的历史教育理论，我们建立了高中历史教学四种研究性学习的模式。
In this paper, a new approach is set forth that integrating both decision tree incremental learning and neural network global learning. Through theory analysis, it's indicated th…
为解决该问题，本文采用了决策树增量学习法和神经网络完全学习相结合的方法。
In this paper, a new approach is set forth that integrating both decision tree incremental learning and neural network global learning. Through theory analysis, it's indicated th…
为解决该问题，本文采用了决策树增量学习法和神经网络完全学习相结合的方法。
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