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可实现对二维数据的聚类，采用了小波去噪的思想，一种基于多文档得图像合并技术。- Can realize the two-dimensional data clustering, Using wavelet denoising thought, Based on multi-document image obtained combining technique.
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可实现对二维数据的聚类，一种基于多文档得图像合并技术，计算加权加速度。- Can realize the two-dimensional data clustering, Based on multi-document image obtained combining technique, Weighted acceleration.
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Document summarizer approach for the text document to do clustering and then do summarization
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可实现对二维数据的聚类，一种基于多文档得图像合并技术，采用波束成形技术的BER计算。- Can realize the two-dimensional data clustering, Based on multi-document image obtained combining technique, By applying the beam forming technology of BE.
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基于欧几里得距离的聚类分析，一种基于多文档得图像合并技术，cordic算法的matlab仿真。- Clustering analysis based on Euclidean distance, Based on multi-document image obtained combining technique, cordic matlab simulation algorithm.
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k-means和k-mediods的JAVA实现。直接读取文档数据，适用于二维数据。-k-means and k-Medoids clustering algorithm JAVA implementation. Document data read directly,suitable for two-dimensional data.
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document of clustering and reusefactor
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matlab实现的DBSCAN聚类分析，通过文件输入数据，不同的颜色代表一类数据(Matlab implementation of DBSCAN clustering analysis, through the document import data, different colors represent a category of data)
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算法思想：提取文档的TF/IDF权重，然后用余弦定理计算两个多维向量的距离来计算两篇文档的相似度，用标准的k-means算法就可以实现文本聚类。源码为java实现(Algorithm idea: extract the TF/IDF weight of the document, then calculate the distance between two multidimensional vectors by cosine theorem, calculate the similarity
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本文件为常见聚类算法测试数据集 ，UCI上常用的聚类算法数据集(This document is a common clustering algorithm test data set.)
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