2016CCF_BDCI_Sougou | 【源码以及PPT分享】2016CCF大数据与计算智能大赛：精准营销中搜狗用户画像挖掘

by coderSkyChen Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | 2016CCF_BDCI_Sougou Summary

2016CCF_BDCI_Sougou is a Python library. 2016CCF_BDCI_Sougou has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However 2016CCF_BDCI_Sougou build file is not available. You can download it from GitHub.

【源码以及PPT分享】2016CCF大数据与计算智能大赛：精准营销中搜狗用户画像挖掘

Support

Quality

Security

License

Reuse

Support

2016CCF_BDCI_Sougou has a low active ecosystem.

It has 189 star(s) with 111 fork(s). There are 9 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 3 have been closed. On average issues are closed in 115 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of 2016CCF_BDCI_Sougou is current.

Quality

2016CCF_BDCI_Sougou has 0 bugs and 111 code smells.

Security

2016CCF_BDCI_Sougou has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

2016CCF_BDCI_Sougou code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

2016CCF_BDCI_Sougou is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

2016CCF_BDCI_Sougou releases are not available. You will need to build from source code and install.

2016CCF_BDCI_Sougou has no build file. You will be need to create the build yourself to build the component from source.

2016CCF_BDCI_Sougou saves you 438 person hours of effort in developing the same functionality from scratch.

It has 1036 lines of code, 65 functions and 10 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed 2016CCF_BDCI_Sougou and discovered the below as its top functions. This is intended to give you an instant insight into 2016CCF_BDCI_Sougou implemented functionality, and help decide if they suit your requirements.

Fit the features of the corpus .
Performs stacking
Build a preprocessor .
Transform the data .
load TRainsform
return train data
Print out the population size .
Strip accents .
Strip accents from a string .
Calculate the frequency of document X .

Get all kandi verified functions for this library.

2016CCF_BDCI_Sougou Key Features

No Key Features are available at this moment for 2016CCF_BDCI_Sougou.

2016CCF_BDCI_Sougou Examples and Code Snippets

No Code Snippets are available at this moment for 2016CCF_BDCI_Sougou.

Community Discussions

No Community Discussions are available at this moment for 2016CCF_BDCI_Sougou.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install 2016CCF_BDCI_Sougou

You can download it from GitHub.
You can use 2016CCF_BDCI_Sougou 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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