| 高维数据特征提取算法的研究及比较 |
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| 引用本文： | 林晓立,陈恩红,任皖英.高维数据特征提取算法的研究及比较[J].计算机科学,2003,30(4):168-170. |
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| 作者姓名： | 林晓立 陈恩红 任皖英 |
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| 作者单位： | 中国科学技术大学计算机系 合肥 230027 |
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| 基金项目： | 国家自然科学基金(60005004)，安徽省自然科学基金(批准号:01042302) |
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| 摘 要： | 1 引言近年来随着科技的发展,出现了越来越多的复杂数据,如多媒体数据、蛋白质数据等。直接对这些高维数据进行诸如聚类、最近邻搜索及可视化等操作,其代价十分昂贵,需要的运算量往往超出机器的容许范围。特征提取的目的旨在对这些数据进行降维,从而大大降低对它们进行各种操作的计算复杂度。
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| 关 键 词： | Bourgain算法 Cofe算法 高维数据特征提取算法 数据集中 数据处理 |
Algorithms of Feature Extraction from High-Dimensional Objects and their Comparisons |
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| LIN Xiao-Li CHEN En-Hong REN Wan-Ying.Algorithms of Feature Extraction from High-Dimensional Objects and their Comparisons[J].Computer Science,2003,30(4):168-170. |
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| Authors: | LIN Xiao-Li CHEN En-Hong REN Wan-Ying |
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| Abstract: | This paper introduces and analyzes several feature extraction algorithms. These algorithms use linear or non-linear feature extraction methods to project high-dimensional objects into lower dimensional space, thus the complexity of the operations upon them, such as clustering, the nearest-neighbor search, visualization and etc can be reduced. The paper also presents some comparative experimental results of these algorithms and analyzes briefly their advantages or shortcomings. |
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| Keywords: | High-dimensional data Feature extraction Dimension reduction |
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