1) one-class SVM
一类支持向量机
1.
In order to reduce the complexity of computation and improve the generalization of two binary-class support vector machines in images steganalysis,this paper brings forward a steganalysis method based on genetic algorithms and multiple one-class SVM.
提出一种基于遗传算法和多超球面一类支持向量机的隐秘图像检测方案。
2.
This paper brings forward a new blind detection algorithm of real-world stego images based on One-class SVM classification,this algorithm uses high-order wavelet packets statistics feature,only trains normal images to establish classification.
针对二类支持向量机分类器在图像密写分析应用中训练步骤复杂与推广性弱的缺点,提出了基于一类支持向量机分类器的真彩隐秘图像盲检测算法,算法选用小波包高阶统计特征,仅对正常图像训练建立分类器。
3.
A method of fault-diagnoses for sensor based on one-class SVM is put forward,which transforms the time-series data from sensor into vector by means of the technology about reproduction in phase-space,and trains normal-action model with one-class SVM and implements fault-diagnoses by finding abnormity data.
提出了一种基于一类支持向量机的传感器故障诊断方法,它利用相空间重构技术将传感器本身获取的相关时序数据转化成矢量,再用一类支持向量机来训练正常行为模型,进而通过发现数据异常来进行故障诊断。
2) 1-SVM
一类支持向量机
1.
Improved kernel method for clustering based on fuzzy 1-SVM;
基于模糊一类支持向量机的核聚类算法
2.
By training one-class SVM(1-SVM) on the samples class by class,a classifier composed of multiple spheres was obtained.
为了提高支持向量机(SVM)多分类器的训练效率,将多球体思想引入有指导学习,对训练样本按类别分别进行一类支持向量机(1-SVM)训练得到多球体分类器。
3) one-class support vector machine
一类支持向量机
1.
Application of one-class support vector machine in tobacco leaves selection;
一类支持向量机在烟叶选择中的应用
2.
It extracted useful visual features and used one-class support vector machine to identify and filter spam.
它提取出有用的形象特征并使用一类支持向量机来过滤垃圾邮件。
3.
To improve the adaptability and effectiveness of recognition on abnormal condition,a self-adaptive alarm method for equipment condition based on one-class support vector machine (OC-SVM) is proposed.
为了提高对异常状态识别的适应性和有效性,提出了一种基于一类支持向量机的设备状态自适应报警方法。
4) OC-SVM
一类支持向量机
1.
The strategy using the combination of OC-SVM and MC-SVM as the classifier in the approach provide an effective approach for the classification of images out of training models and system\'s expansibility.
采用OC-SVM(一类支持向量机)和MC-SVM(多类支持向量机)联合的策略进行图像来源分类,有效地解决了对未知模型图像来源的鉴别问题以及可扩展性差的问题。
5) Hypersphere One-class Support Vector Machines
一类超球面支持向量机
1.
Aim at limited samples learning and hard sampling of foreign body because of its complexity and variety, Hypersphere One-class Support Vector Machines was pres
深入研究了支持向量机原理,针对物料样本有限和异物样本复杂多样难以采集的现象,提出了一类超球面支持向量机异物识别算法;提出了D-QDPSO优化算法,进行OC-SCM的求解,减小了误识率。
6) fuzzy one-class support vector machine
模糊一类支持向量机
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