1) dynamically constructed nearest neighbor graph
动态k近邻图
1.
After profound study of the informative nearest neighborhood and its indication of the boundary of clusters, a dynamically constructed nearest neighbor graph is proposed to find different location model of points.
通过分析和挖掘最近邻关系中所包含的丰富信息,深入挖掘最近邻关系的不对称性在簇边界识别中的指示作用,设计和构造了动态k近邻图和基于密度模式的簇扩展机制,将密度模式的表示、簇边界的识别、簇内成员点扩展等环节在统一的模型下进行解决。
2) k-nearest neighbor graph
k-近邻图
4) k-nearest neighbor hyper-graph
k-近邻超图
1.
k-nearest neighbor hyper-graph is used to represent the content relations among shots, and shots are clustered based on hyper-graph model.
它采用k-近邻超图描述镜头间的内容相似关系,利用超图模型对镜头聚类,并通过分析镜头类别间的时间投影关系提取故事单元,并采用一维字符串描述故事单元。
5) K-nearest neighbor
K-最近邻
1.
Development and improvement of K-Nearest Neighbor clustering technique
K-最近邻分类技术的新发展与技术改进
2.
To further understand the quantitative structure-activity relationship(QSAR)of fluorine-containing pesticide and improve the prediction precision of QSAR models,a novel nonlinear combinatorial forecast me-thod named Multi-KNN-SVR,multi-K-nearest neighbor based on support vector regression,was proposed.
为深入认识含氟农药生物活性与其结构之间的关系,建立了理想的QSAR模型,从化合物油水分配系数等7个分子结构描述符出发,基于支持向量回归(SVR)和MSE最小原则,经自动寻找最优核函数和非线性筛选描述符,构建了多个K-最近邻(KNN)预测子模型。
3.
In order to improve the predication precision of quantitative structure-activity relationship(QSAR) model,a novel combinatorial k-nearest neighbor method based on support vector machine regression(SVR-CKNN) was proposed,which could screen descriptors automatically and then builds several k-nearest neighbor models for combinatorial forecast.
该法基于支持向量机回归(SVR)自动筛选化合物结构描述符,以k-最近邻建立多个子模型实施组合预测(CKNN)。
6) K-nearest neighbor
K近邻
1.
Phosphorylation Site Prediction Based on k-Nearest Neighbor Algorithm and BLOSUM62 Matrix;
基于k近邻和BLOSUM62矩阵方法的磷酸化位点预测
2.
Facial expression recognition based on C-means and K-nearest neighbor algorithms;
基于C均值K近邻算法的面部表情识别
3.
A promising K-nearest neighbor nonparametric regression forecasting model based on typical historical database was developed.
基于所构建的历史数据库,通过数值试验,确定了状态向量、距离匹配原则,K近邻值等参量,构建了一种基于K近邻的非参数回归短时交通预测模型,实现了对路段行程速度的短时预测。
补充资料：动态
①（事情）变化发展的情况：科技～ㄧ从这些图片里可以看出我国建设的～。②艺术形象表现出的活动神态：画中人物，～各异，栩栩如生。③运动变化状态的或从运动变化状态考察的：～工作点ㄧ～电流ㄧ～分析。
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