kmean_model | # # 使用kmeans模型对新闻数据进行聚类 # 使用简要说明 python test

 by   ldanduo Python Version: Current License: No License

kandi X-RAY | kmean_model Summary

kandi X-RAY | kmean_model Summary

kmean_model is a Python library. kmean_model has no bugs, it has no vulnerabilities and it has low support. However kmean_model build file is not available. You can download it from GitHub.

##使用kmeans模型对新闻数据进行聚类 #使用简要说明 python test.py word_dict.txt center_file.txt input_data.txt output_file.txt word_dict.txt : 新闻词带,即统计语料中的词频率,去掉单字以及只出现一次的词 center_file.txt : 从语料中抽取5篇作为初始的中心点。为了效果明显,每类别中选取一篇作为初始中心。 input_data.txt : 已用空格进行了分词,每一行代表一篇文件。 output_file.txt : 输出文件.
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              kmean_model has a low active ecosystem.
              It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
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              It had no major release in the last 6 months.
              kmean_model has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of kmean_model is current.

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              kmean_model has no bugs reported.

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              kmean_model has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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              kmean_model does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              kmean_model releases are not available. You will need to build from source code and install.
              kmean_model has no build file. You will be need to create the build yourself to build the component from source.

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            Install kmean_model

            You can download it from GitHub.
            You can use kmean_model like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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