tencent_ad | Tencent Social Advertising Algorithm Competition

by loyalzc Python Version: Current License: No License

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

kandi X-RAY | tencent_ad Summary

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

Tencent Social Advertising Algorithm Competition 2018

Support

Quality

Security

License

Reuse

Support

tencent_ad has a low active ecosystem.

It has 41 star(s) with 13 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 0 have been closed. On average issues are closed in 872 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tencent_ad is current.

Quality

tencent_ad has 0 bugs and 0 code smells.

Security

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

tencent_ad code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

tencent_ad 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.

Reuse

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

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

tencent_ad saves you 485 person hours of effort in developing the same functionality from scratch.

It has 1141 lines of code, 63 functions and 20 files.

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

Top functions reviewed by kandi - BETA

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

Read and test data
Base processing
Base classifier
Convert base word into a vector
Get lp data
Calculate the score for a feature
Combine features
Combine two features
Cross 3 feature
Compute the cross product between two features
Get feature
Base word2vec
Generate random features
Returns the best scores for features
Get k - means features from vector features
Retrieve the topk features in the corpus
Run LGBM classification
Get kmeans feature feature
The base cross feature
Select cross 3 features
Select cross feature
Get test data
Get one - hot feature

Get all kandi verified functions for this library.

tencent_ad Key Features

No Key Features are available at this moment for tencent_ad.

tencent_ad Examples and Code Snippets

No Code Snippets are available at this moment for tencent_ad.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install tencent_ad

You can download it from GitHub.
You can use tencent_ad 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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