1) single layer clustering
单层聚类
1.
By using this measure, two hierarchical multi-category SVMs, binary-Tree SVMs and single layer clustering SVMs, are presented.
针对支撑向量机的特点提出了一种特征空间中的类间可分性度量 ,并基于该度量通过聚类算法构造了二叉树和单层聚类两种层次型多类支撑向量机。
2) Word Clustering
单词聚类
1.
This paper evaluates four unsupervised Chinese word clustering methods.
本文对无监督的中文单词聚类方法进行了比较研究,包括最大化平均互信息(MMI),基于功能词的聚类(FW),基于高频词的聚类(HFW)以及基于词类的聚类(WC)。
3) single-pass clustering
单遍聚类
1.
The proposed algorithms based on single-pass clustering,the computation overhead is optimized by introducing topic center.
提出了基于多中心模型的网络热点话题发现算法,利用话题中心判别新出现的报道是否属于已有网络话题,算法基于单遍聚类思想,通过引入话题中心的策略优化了算法的计算开销。
4) hierarchical clustering
层次聚类
1.
Small targets detection based on hierarchical clustering;
基于层次聚类的弱小目标检测算法
2.
A new hierarchical clustering algorithm based on tree edit distance;
基于树编辑距离的层次聚类算法
3.
Combined unsupervised image segmentation using watershed and hierarchical clustering with MRF;
分水岭算法和基于MRF的层次聚类相结合的混合无监督图像分割算法
5) hierarchical clustering
分层聚类
1.
Research of general purpose computation on hierarchical clustering algorithm using graphics processing unit;
图形处理器在分层聚类算法中的通用计算研究
2.
A new method called hierarchical clustering queries system is presented.
提出一种基于结构化P2P的分层聚类查询系统。
3.
In order to explore the ability to identify different tree species in different bands, the field spectrometry instrumentation was used to measure hyperspectral data of four different tree species, such as sha mu,xue song,zhang shu and gui hua in this research, and stepwise discriminant analysis and hierarchical clustering were used to analyse the experime.
研究采用了逐步判别分析法和分层聚类法对实验数据进行数据分析。
6) hierarchical cluster
层次聚类
1.
Based on the multi-dimensional approximate periodic pattern, we present an algorithm to mine multi-dimensional temporal approximate periodicity with the algorithm of hierarchical cluster, then applies to the stock data.
在多维时态近似周期模型的基础上,提出了一种基于时态数据库技术和层次聚类技术的多维时态近似周期挖掘算法,并应用于股票数据。
2.
An equivalence relation ≡HCov is proposed based on the Data Cube s semantics and the dimension s hierarchy of its pattern, and then on the basis of the equivalence relation, proceeds the data cube to hierarchical cluster.
在DataCube语义特性及模式中维的层次性基础上提出了多维数据之间的等价关系≡HCov,对DataCube进行层次聚类·该方法的优点在于用等价类的方法保存了所有聚集记录,同时定义了等价类之间的关系,以保存聚集记录之间的层次信息·理论分析和实验证明,该方法不但节省了存储空间,而且利用聚类信息及层次信息,可高效的进行各种OLAP查询,以及支持多维数据上的上钻下钻、旋转等Cube语义操作·同时,为OLAP查询导航、OLAP查询行为分析的实现提供了可能
3.
The result, normally overpredicted by traditional Environment Envelope Model, is improved by using hierarchical cluster arith- metic that can reduce the influence caused by outliers.
在这一系统中,通过层次聚类算法对物种已知分布点数据进行处理,减少了异常值对预测结果的影响,从而解决了环境包络模型预测结果过于乐观的问题,在物种已知分布数据较少时也能取得较好的结果。
补充资料：-羟基-聚氧乙烯单-C12-13-烷基醚磷酸钾盐类
CAS：68130-44-9
中文名称：α-氢-ω-羟基-聚氧乙烯单-C12-13-烷基醚磷酸钾盐类
英文名称：Poly(oxy-1,2-ethanediyl), .alpha.- hydro-.omega.-hydroxy-, mono-C12-13-alkyl ethers, phosphates, potassium salts
poly(oxy-1,2-ethanediyl), alpha-hydro- omega-hydroxy-, mono-c12-13-alkyl ethers, phosphates, potassium salts
Poly(oxy-1,2-ethanediyl),.alpha.-hydro-.omega.-hydroxy-,mono-C12-13-alkyl ethers,phosphates,potassium salts
中文名称：α-氢-ω-羟基-聚氧乙烯单-C12-13-烷基醚磷酸钾盐类
英文名称：Poly(oxy-1,2-ethanediyl), .alpha.- hydro-.omega.-hydroxy-, mono-C12-13-alkyl ethers, phosphates, potassium salts
poly(oxy-1,2-ethanediyl), alpha-hydro- omega-hydroxy-, mono-c12-13-alkyl ethers, phosphates, potassium salts
Poly(oxy-1,2-ethanediyl),.alpha.-hydro-.omega.-hydroxy-,mono-C12-13-alkyl ethers,phosphates,potassium salts
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