But it exists the limitation of memory for high-dimension data. So a deeply research will be continued.
但是，对高维数据的 分类，存在内存受限的问题，还需要进一步的深入研究。
参考来源 - 数据挖掘分类算法的研究与应用·2,447,543篇论文数据，部分数据来源于NoteExpress
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 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。
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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