1) Reverse K Nearest Neighbors(RKNN)
反向K近邻
2) Reverse k nearest neighbors
反k近邻
1.
Stream data Outlier Mining algorithm based on Reverse k Nearest Neighbors(SOMRNN) is proposed according to the concept that reverse k nearest neighbors is suitable to measure outlier degree.
反k近邻适用于度量离群程度,根据该性质提出基于反k近邻的流数据离群点挖掘算法(SOMRNN)。
3) reverse nearest neighbor
反向最近邻
1.
To effectively solve reverse nearest neighbor queries in a dataset,the properties of the Voronoi diagram and space-dividing regions were used to evaluate the reverse nearest neighbors of the given query points.
为了解决数据集中数据点的反向最近邻问题,利用Voronoi图及空间分割区域的性质计算查询点的反向最近邻,通过Voronoi图的特性可免去每次都计算数据集中给定查询点的最近邻的步骤,每次查询可过滤出少数的几个数据点并对其进行反向最近邻的判断。
2.
With the rapid development of wireless communications,the applications of reverse nearest neighbor for moving objects are more wide.
针对现有的算法,很多观点都是基于静态对象的,提出以TPR-tree为索引结构,用现有的半平面修剪策略进行改进的,利用剩余MBR的对角线判断是否保留MBR的方法,使原修剪策略性能优化,并采用过滤提纯的方法来获取移动查询点的反向最近邻,实现了移动对象的动态反向最近邻查询。
3.
Nowadays,many reverse nearest neighbor search methods are based on static objects.
针对现有反向最近邻算法很多都是基于静态对象的情况,提出了一种新的基于移动对象的反向最近邻的算法——以TPR-tree为索引结构,对原有的半平面修剪策略进行了改进,使其性能优化,并采用过滤验证这两个处理步骤来获取移动查询点的反向最近邻,实现了移动对象的动态反向最近邻的查询。
4) 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)。
5) 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。
6) k-near neighbor group
k-近邻群
1.
A novel combinatorial forecast method based on support vector machine regression and k-near neighbor group and its application in QSAR;
基于SVR和k-近邻群的组合预测在QSAR中的应用
补充资料：Nearestneighbor(近邻取样)
nearest neighbor (近邻取样)
又被称为point sampling(点取样)，是一种较简单材质影像插补的处理方式。会使用包含像素最多部分的图素来贴图。换句话说就是哪一个图素占到最多的像素，就用那个图素来贴图。这种处理方式因为速度比较快，常被用于早期3d游戏开发，不过材质的品质较差。
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