ranked_prediction | Machine learning project | Machine Learning library

by arilato Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | ranked_prediction Summary

ranked_prediction is a Python library typically used in Manufacturing, Utilities, Machinery, Process, Artificial Intelligence, Machine Learning applications. ranked_prediction has no bugs, it has no vulnerabilities and it has low support. However ranked_prediction build file is not available. You can download it from GitHub.

Machine learning project on predicting ranked game outcomes based on data available in champion select.

Support

Quality

Security

License

Reuse

Support

ranked_prediction has a low active ecosystem.

It has 23 star(s) with 5 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 812 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of ranked_prediction is current.

Quality

ranked_prediction has 0 bugs and 0 code smells.

Security

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

ranked_prediction code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

ranked_prediction 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

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

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

ranked_prediction saves you 333 person hours of effort in developing the same functionality from scratch.

It has 798 lines of code, 25 functions and 4 files.

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

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ranked_prediction Key Features

No Key Features are available at this moment for ranked_prediction.

ranked_prediction Examples and Code Snippets

No Code Snippets are available at this moment for ranked_prediction.

Community Discussions

Trending Discussions on ranked_prediction

BigQuery argmax: Is array order maintained when doing CROSS JOIN UNNEST

QUESTION

BigQuery argmax: Is array order maintained when doing CROSS JOIN UNNEST

Asked 2018-Dec-05 at 17:54

Question:

In BigQuery, standard SQL, if I run

...

ANSWER

Answered 2018-Dec-05 at 17:42

Seems like it keeps the ordering of array intact, by default.

However, one possible way to be 100% sure is to impose some sort of insignificant sorting, which will tell the query processor in the BQ blackbox to not use any sort of default ordering if it tries to.

Something like:

Source https://stackoverflow.com/questions/53635020

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

Vulnerabilities

No vulnerabilities reported

Install ranked_prediction

You can download it from GitHub.
You can use ranked_prediction 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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