Grid-based division approach for high-dimensional data space

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (5): 152-153.

• 数据库、信号与信息处理 • Previous Articles Next Articles

Grid-based division approach for high-dimensional data space

HE Ling¹，CAI Yichao¹，YANG Zheng²

1.Department of Early Warning Surveillance Intelligence，Air Force Radar Academy，Wuhan 430019，China
2.School of Information System and Management，National University of Defense Technology，Changsha 410073，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-02-11 Published:2011-02-11

高维数据空间的一种网格划分方法

贺玲¹，蔡益朝¹，杨征²

1.空军雷达学院预警监视情报系，武汉 430019
2.国防科技大学信息系统与管理学院，长沙 410073

Abstract

Abstract: In order to avoid the curse of dimensionality，it is efficient to deal with high-dimensional data in proper subspaces.This paper puts forward a new idea to form subspaces by dividing high dimensional space into grids，and each dimension is divided into depth-equal grids.The pretreatment of high dimensional data establishes necessary base for succeeding analysis.

Key words: curse of dimensionality, subspace, grid-based division

摘要： 在高维数据空间的子空间中对高维数据进行处理是减小甚至消除“维度灾难”的一个有效方法。为选择合理的子空间，提出了一种基于网格划分的子空间生成方法。在考虑数据集整体分布的前提下，对各维数据进行等深度的区间划分，为高维数据的后续相关处理奠定了良好的基础。

关键词: 维度灾难, 子空间, 网格划分

HE Ling¹，CAI Yichao¹，YANG Zheng². Grid-based division approach for high-dimensional data space[J]. Computer Engineering and Applications, 2011, 47(5): 152-153.

贺玲¹，蔡益朝¹，杨征². 高维数据空间的一种网格划分方法[J]. 计算机工程与应用, 2011, 47(5): 152-153.

[1]	SANG Jianghui, JIANG Haiyan. Multi-label Transfer Learning Algorithm Based on Joint Distribution Alignment [J]. Computer Engineering and Applications, 2021, 57(9): 154-161.
[2]	MA Yang, ZHAO Xujun. Multi-source Outlier Detection Algorithm Based on Relevant Subspace [J]. Computer Engineering and Applications, 2021, 57(17): 88-95.
[3]	HU Wentao, CHEN Xiuhong. Robust Sparse Subspace Learning Based on Locality Preserving Projections [J]. Computer Engineering and Applications, 2021, 57(10): 194-199.
[4]	DONG Yanhua, ZHANG Shumei, ZHAO Junli. Review of Occlusion Face Recognition Method [J]. Computer Engineering and Applications, 2020, 56(9): 1-12.
[5]	WANG Yusi, LU Deyang, LI Haiyang. Sparse Subspace Clustering Method Based on Fractional Function Constraints [J]. Computer Engineering and Applications, 2020, 56(7): 39-47.
[6]	WANG Yiwu, YANG Yuwang. Research and Application of Spatial Projection in [K]-means Algorithm [J]. Computer Engineering and Applications, 2020, 56(7): 200-204.
[7]	ZHENG Yi, MA Yingcang, YANG Xiaofei, XU Qiuxia. Sparse Subspace Clustering Based on [k]-Nearest Neighbors and Local Similarity [J]. Computer Engineering and Applications, 2020, 56(4): 99-108.
[8]	JIN Hongqi, CHEN Xindu, WU Lei. Defect Detection Combining Random Subspace and Cascade Residual Network [J]. Computer Engineering and Applications, 2020, 56(23): 265-269.
[9]	ZHU Dan, CHEN Xiaohong, WU Qingyuan, LI Shunming. Subspace Clustering Induced by Adaptive Graph Learning [J]. Computer Engineering and Applications, 2020, 56(21): 30-37.
[10]	QIN Fengting, YANG Youlong, QIU Haiquan. Sparse Subspace-Based Method for Local Outlier Detection [J]. Computer Engineering and Applications, 2020, 56(19): 152-159.
[11]	GUO Sheng, ZHONG Zhaoman, LI Cunhua. Multi-view Subspace Clustering Network Based on Deep Autoencoder [J]. Computer Engineering and Applications, 2020, 56(17): 60-68.
[12]	LIU Wenfen, MU Xiaodong, HUANG Yuehua. Anomaly Detection Method Based on Multi-resolution Grid [J]. Computer Engineering and Applications, 2020, 56(17): 78-85.
[13]	LI Dan. Structured Weighted Correlation Adaptive Subspace Clustering [J]. Computer Engineering and Applications, 2020, 56(13): 137-142.
[14]	YANG Ying, WANG Jun, WANG Gang. Customer Complaints Classification Method Based on Improved Random Subspace [J]. Computer Engineering and Applications, 2020, 56(13): 230-235.
[15]	CHEN Liang, PAN Haipeng, WU Ping, ZHOU Wei. Closed Loop Subspace Identification Method of Impulse Response Model [J]. Computer Engineering and Applications, 2019, 55(8): 195-200.

Grid-based division approach for high-dimensional data space

高维数据空间的一种网格划分方法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics