Venkatasubramanian and colleagues performed a series of tests of their new method with "synthetic data" - data points in a "high-dimensional space."
文卡和同事们用“模拟数据”(“高维空间”的数据点)完成了这种新方法的一系列测试。
By designing projection index it projects high dimensional data set to low dimensional space to reveal the internal structures and characters of high dimensional dataset.
投影寻踪方法是根据特定的应用意义设计相应的投影指标，把高维数据集投影到低维数据空间后进行分析，揭示高维数据集内部的结构和特征。
Venkatasubramanian and colleagues performed a series of tests of their new method with "synthetic data" - data points in a "high-dimensional space. "
文卡和同事们用“模拟数据”（“高维空间”的数据点）完成了这种新方法的一系列测试。
The data points in high dimensional space were mapped into corresponding data points in lower dimensional space under preserving distance between data points.
并在保持各数据点临近位置关系情况下，把高维空间数据点映射为低维空间对应的数据点。
The SVM (Support vector Machine) classifies the data by mapping the vector from low-dimensional space to high-dimensional space using kernel function.
而SVM(支持向量机)引进核函数隐含的映射把低维特征空间中的样本数据映射到高维特征空间来实现分类。
The sparsity and the problem of the curse of dimensionality of high-dimensional data, make the most of traditional clustering algorithms lose their action in high-dimensional space.
高维数据的稀疏性和“维灾”问题使得多数传统聚类算法失去作用，因此研究高维数据集的聚类算法己成为当前的一个热点。
Quotient space theory for treatment of high-dimensional, incomplete, complex, vague, massive data, there are unique advantages.
商空间理论在处理高维、不完备、复杂的、模糊的、海量数据时，有其独特的优势。
Quotient space theory for treatment of high-dimensional, incomplete, complex, vague, massive data, there are unique advantages.
商空间理论在处理高维、不完备、复杂的、模糊的、海量数据时，有其独特的优势。
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