The query of High dimension data attracts more and more attention.
目前，高维数据的快速检索问题已经受到越来越多的关注。
A combined optimization decision tree algorithm suitable for a large scale and high dimension data-base is presented.
提出了一种适合于大规模高维数据库的组合优化决策树算法。
The effectiveness and efficiency of the algorithms have been shown by experimental results, especially for the high dimension data warehouses.
实验证明了一系列算法的效率和有效性，尤其适合数据仓库中的高维数据集。
Compared with some other modeling methods, such as ANFIS, the proposed model is of less computation, higher accuracy, especially for high dimension data modeling.
与其他建模方法相比，如anfis，模糊树模型计算量小，精度高，尤其在高维数据建模中更为明显。
These strings of hundreds of attributes are called high-dimensional data because each attribute is called one dimension.
文卡说道，“这些包含数百项属性的字符串就称为高维（high-dimensional）数据，而每一项属性就是一维。
Realizes high, dimension data feature extraction algorithm by using debasing dimension of data.
实现了基于数据降维的高维数据特征提取算法。
Mixtures of factor analyzers, is a nonlinear tool for high-dimension data.
混合因子分析模型是一种非线性的分析高维数据的工具。
The paper introduces the calculation method of the associative dimension for high-precision gravity field. The trial computation results of models and real data are also given.
文章介绍了高精度重力场关联维的计算方法，并给出了模型与实际资料的试算结果。
The results showed that the restraint variable-dimension method not only could have high calculation accuracy and good numeric stability but also have certain data noise control capability.
识别结果表明，约束变尺度方法不仅具有较高的计算精度和良好的数值稳定性，并且具有一定的抑制数据噪音的能力。
An example presented in the paper demonstrates that this reduction of dimension makes the high-resolution inversion of the normal well logging data possible.
实例计算表明，这种降维方法使测井资料高分辨率反演成为可能。
As a result, when doing data mining on high dimensional data, it is necessary to reduce the dimension of primal data at first.
因此，对高维数据进行数据挖掘时，必须先对原始数据进行降维处理。
To analysis the sample data space by PCA can assume that it can lower the dimension of high variant space and eliminate the relativity of sample data.
通过对样本数据空间的主成分分析，能够保证在信息损失最少的情况下，对高维变量空间进行降维处理，减少样本数据间的相关性。
The high generalization ability of Support Vector Machine (SVM) makes it especially suitable for the classification of high-dimension data such as term-document.
支持向量机(SVM)高度的泛化能力使它特别适用于高维数据例如文档的分类。
The intrinsic dimension estimation of high-dimensional data, is important in the field of high-dimensional data processing.
高维数据的本征维数估计问题研究，在高维数据处理领域中有着重要的地位。
We proposed a paper sheet defects classification method based on SVM according to its good performance in small data sets and high dimension feature Spaces.
根据支持向量机(SVM)在小样本、高维模式分类中具有的优良分类性能，提出将支持向量机应用于实际的纸张缺陷分类。
The algorithm could solve the problems of 1)large volume of data set; 2)data set of high dimension;
该基于超图的高维聚类算法具有以下特点：1）能处理大数据集；
Also we construe the high data dimension and entropy of hyperspectral image.
高光谱图像的特性是对高光谱图像进行压缩的基础。
Based on a method of 2 dimension data rearrange, a high speed and high efficiency implementation of DRAM access is proposed in the design of block buffer manager.
在数据块缓冲管理器的设计中，采用一种基于二维数据重排的访问方式，实现高速高效的DRAM访问。
Adaptive Random Testing (ART) is an enhanced version of Random Testing (RT). There are two factors that restrict the performance of ART, high-dimension data and distance metric.
针对自适应随机测试(ART)存在的高维和距离度量问题，提出一种改进的软件自适应随机测试策略。
Adaptive Random Testing (ART) is an enhanced version of Random Testing (RT). There are two factors that restrict the performance of ART, high-dimension data and distance metric.
针对自适应随机测试(ART)存在的高维和距离度量问题，提出一种改进的软件自适应随机测试策略。
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