Description: 神经网络中的K均值聚类算法II：
1.KMIn为输入数据文本，其中，第一个参数为所要聚类点个数，第二个参数为聚类点的维数,第三个参数为所要求聚类的个数
2.KM2OUT为经过K均值聚类算法II计算后得到的结果-Neural network in K-means clustering algorithm II: 1.KMIn input data for the text, of which the first parameter to be the number of clustering points, the second parameter is the dimension of clustering points, the third parameter for the clustering the number of requests for 2.KM2OUT after K-means clustering algorithm II calculation results Platform: |
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Author:blue8202 |
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Description: 类似于Weka的文本聚类工具箱，可以读取Weka格式的文件，并实现了常用的文本聚类算法以及聚类集成算法，对于机器学习的朋友来说是个好东西-Similar to the text clustering toolbox Weka, Weka can read the file format and realize the common text clustering algorithm, as well as integrated clustering algorithm for machine learning of a friend is a good thing Platform: |
Size: 3512320 |
Author:叶云龙 |
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Description: kmeans文本聚类算法的简单实现，是用JAVA实现的-kmeans a simple realization of the text clustering algorithm is implemented using JAVA Platform: |
Size: 11264 |
Author:rocky |
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Description: 文本聚类算法源码，包含tf.idf计算的实现，采用java语言编写-text cluster algorithm, including the computation of tf.idf ,written by Java Platform: |
Size: 9216 |
Author:谭磊 |
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Description: 对文本聚类的向量空间模型机制VSM以及Kmeans等讲解比较详细，是研究文本聚类的好书籍-Clustering of text vector space model to explain the mechanism of VSM and Kmeans and other more detailed, study of text clustering is a good book Platform: |
Size: 2488320 |
Author:zhan |
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Description: java实现kmeans算法，可以处理任意维度的向量。并将聚类结果写入文本。-The kmeans algorithm java, and can handle any dimension vector. And write text clustering results. Platform: |
Size: 693248 |
Author:武夷河 |
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Description: 基于KMeans的文本聚类算法，支持文本输入，简单易懂-KMeans clustering algorithm based on text, support for text input, easy to understand Platform: |
Size: 20480 |
Author:sean |
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Description: k-means算法是文本聚类经典算法，也是数据挖掘十大经典算法之一。k-means算法Java实现。-k-means algorithm is a classical algorithm text clustering, data mining is one of the ten classic algorithms. k-means algorithm is implemented in Java. Platform: |
Size: 2048 |
Author:黄紫竹 |
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Description: 本文档描述了TF-IDF和kmeans的详细实现原理和实现步骤-the doucument descripe the principle and step of TF-IDF and kmeans Platform: |
Size: 35840 |
Author:blue |
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Description: 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 of the two documents, and achieve the text clustering with the standard k-means algorithm. Source code for Java implementation) Platform: |
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Author:startrek
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Description: jieba分词将中文文本进行分词处理，将分词后的结果使用word2vec转化成词向量，使用kmeans将中文文本进行聚类(Jieba participle segmenting Chinese text, transforming the result of word segmentation into word vector using word2vec, and clustering Chinese text using kmeans.) Platform: |
Size: 3072 |
Author:zxy0308 |
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Search - kmeans text clustering