计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (8): 135-137.
• 数据库、信号与信息处理 • 上一篇 下一篇
柴 毅1，利 节1，唐 婧2
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CHAI Yi1，LI Jie1，TANG Jing2
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摘要： 由于高维数据聚类的现实意义日益增强，而Parzen窗估计法仅对低维数据集聚类能获得良好的结果，随着维数增加，效率降低，因此对Parzen窗进行加权改进，通过多次仿真实验确定加权函数，将高维数据投射至低维空间，对其聚类，逐步投向高维空间，对结果矩阵进行优化处理，得到更为优良的聚类效果。
关键词: 高维数据, Parzen窗, 聚类
Abstract: Due to the realistic meaning of clustering on high-dimension dataset，excellent result can be acquired when clustering dataset using traditional Parzen window on low-dimension.With the higher dimension，the efficiency decreases quickly.Through many simulate experiments，the weighting function is gained.The high-dimension dataset is shadowed on lower-dimensional space，and clustered，then shadowed back to higher-dimensional space.The result matrix is optimized，and the better clustering effect is gained.
Key words: high-dimensional dataset, Parzen window, clustering
柴 毅1，利 节1，唐 婧2. 改进Parzen窗解决高维数据聚类的方法研究[J]. 计算机工程与应用, 2011, 47(8): 135-137.
CHAI Yi1，LI Jie1，TANG Jing2. Study of clustering using improved Parzen window on high-dimension dataset[J]. Computer Engineering and Applications, 2011, 47(8): 135-137.
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