Absrtact: SVM (support vector machine) algorithm is the newest branch of statistic learning theory.
摘要：支持向量机(SVM)算法是统计学习理论中最年轻的分支。
Support vector machine is a new machine learning algorithm, based theoretically on statistic learning theory created by Vapnik.
为了系统地归纳统计学习理论与支持向量机的基本思想和算法，总结目前该领域的最新研究成果。
Thus, combined with research results of statistic learning theory, the optimal regress model based on least-absolute criteria, or LaOR model was proposed to solve the problem.
为此，结合统计学习理论的研究成果，建立了基于最小一乘准则的最优回归模型，并将其应用于商业银行的信贷风险评估中。
At present, most of video semantic annotation methods are based on statistic theory. The methods use supervised learning method to do semantic label.
目前已有的视频语义标注方法多是基于统计学理论，采用全监督学习方法进行语义标注工作。
Comparing with the models based on multiple statistic analysis, generalized regress-ion neural network or adapted fuzzy neural network model, it shows better learning precision and generalization.
与多元线性回归、模糊回归和自适应模糊神经网络相比，该模型学习精度高且具有较好的泛化能力，能取得较好的预测效果。
Through statistic of questionnaires we find that students with better information literacy performance better in English learning.
通过对学生信息素养调查问卷统计我们看到信息素养好的学生英语成绩也普遍较高。
Through statistic of questionnaires we find that students with better information literacy performance better in English learning.
通过对学生信息素养调查问卷统计我们看到信息素养好的学生英语成绩也普遍较高。
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