2) decision-tree-based support vector machine
决策树型支持向量机
1.
At first, the authors quickly clear the disturbing regions using shape based moments on the basis of particular color and regular geometrics of traffic signs, then make remaining regions standard and input them into decision-tree-based support vector machine which well worked to recognize.
首先根据交通标志特殊颜色信息和规则几何外形,利用边界矩技术迅速清除干扰区域,然后将剩下的区域规格化,送入训练好的决策树型支持向量机识别。
4) support vector machine
支持向量机算法
1.
A newly proposed technique of data mining, called "support vector machine" , is suitable for the data mining of ill-posed.
近年来新提出的“支持向量机算法”适合于处理不适定问题,能限制过拟合,且因采用核函数算法,能有效处理非线性数据集,与当前化学化工中应用极广的人工神经网络相比,优越性明显,在化学化工中具有巨大的应用潜力。
2.
And the data of Al, Ca, Cu, Zn, Mg contents have been processed by a new data mining algorithm, support vector machine proposed by Vapnik, in order to search the correlation between these data and high blood pressure disease.
计算表明:支持向量机算法建模的正确分类率和留一法预报正确率均较Fisher法和KNN法等传统的模式识别算法高。
3.
By using leaving-one method, it has been found that the prediction ability of the mathematical modei made by support vector machine is better than that made by Fisher method or KNN method.
本工作应用支持向量机算法总结实验数据的数学模型,并用留一法检验模型的预报能力。
5) DSS algorithm
决策支持DSS算法
6) decision-directed acyclic graph SVM
有向无环图决策支持向量机
补充资料：支持向量机方法
支持向量机(SVM)是90年代中期发展起来的基于统计学习理论的一种机器学习方法，通过寻求结构化风险最小来提高学习机泛化能力，实现经验风险和置信范围的最小化，从而达到在统计样本量较少的情况下，亦能获得良好统计规律的目的。支持向量机算法是一个凸二次优化问题,能够保证找到的极值解就是全局最优解，是神经网络领域域取得的一项重大突破。与神经网络相比，它的优点是训练算法中不存在局部极小值问题，可以自动设计模型复杂度(例如隐层节点数)，不存在维数灾难问题，泛化能力强。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条