rnn_cws | chinese word segmentation based on rnn
kandi X-RAY | rnn_cws Summary
kandi X-RAY | rnn_cws Summary
rnn_cws is a Python library. rnn_cws has no bugs, it has no vulnerabilities and it has low support. However rnn_cws build file is not available. You can download it from GitHub.
说明: 利用rnn实现中文分词算法 源码参考:数据集下载地址:训练步骤: 1 用现有的语料库(已经切分好)训练出word2vec的model 2 预训练处理语料库得到训练输入和测试输入 3 构建rnn并进行训练,在训练的同时测试准确率 4 根据训练好的model得到可能的序列组合,并利用viterbi算法选择出其中可能性最大的一个序列.
说明: 利用rnn实现中文分词算法 源码参考:数据集下载地址:训练步骤: 1 用现有的语料库(已经切分好)训练出word2vec的model 2 预训练处理语料库得到训练输入和测试输入 3 构建rnn并进行训练,在训练的同时测试准确率 4 根据训练好的model得到可能的序列组合,并利用viterbi算法选择出其中可能性最大的一个序列.
Support
Quality
Security
License
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Support
rnn_cws has a low active ecosystem.
It has 14 star(s) with 5 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
There are 0 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of rnn_cws is current.
Quality
rnn_cws has no bugs reported.
Security
rnn_cws has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
rnn_cws does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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rnn_cws releases are not available. You will need to build from source code and install.
rnn_cws has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed rnn_cws and discovered the below as its top functions. This is intended to give you an instant insight into rnn_cws implemented functionality, and help decide if they suit your requirements.
- Example example
- Computes the Viterbi
Get all kandi verified functions for this library.
rnn_cws Key Features
No Key Features are available at this moment for rnn_cws.
rnn_cws Examples and Code Snippets
No Code Snippets are available at this moment for rnn_cws.
Community Discussions
No Community Discussions are available at this moment for rnn_cws.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install rnn_cws
You can download it from GitHub.
You can use rnn_cws 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.
You can use rnn_cws 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.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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