nba-prediction | nba prediction based LogisticRegression by sklearn | Machine Learning library

by 395299296 Python Version: Current License: No License

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

kandi X-RAY | nba-prediction Summary

nba-prediction is a Python library typically used in Artificial Intelligence, Machine Learning, Pytorch applications. nba-prediction has no bugs, it has no vulnerabilities and it has low support. However nba-prediction build file is not available. You can download it from GitHub.

intall package: pip3 install pandas pip3 install sklearn pip3 install scipy.

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Support

nba-prediction has a low active ecosystem.

It has 3 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

nba-prediction has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of nba-prediction is current.

Quality

nba-prediction has 0 bugs and 0 code smells.

Security

nba-prediction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

nba-prediction code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nba-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

nba-prediction releases are not available. You will need to build from source code and install.

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

Train model using logistic regression
Builds a data set from team stats
Calculates the winner and loser ranks
Predict the winner of a team
Get elo for team

Get all kandi verified functions for this library.

nba-prediction Key Features

No Key Features are available at this moment for nba-prediction.

nba-prediction Examples and Code Snippets

No Code Snippets are available at this moment for nba-prediction.

Community Discussions

Trending Discussions on nba-prediction

Python 'int' object is not iterable when using len on a list from beautifulsoup

QUESTION

Python 'int' object is not iterable when using len on a list from beautifulsoup

Asked 2020-Jan-28 at 00:40

So far I have the following code, I'm including all of it in case it helps

...

ANSWER

Answered 2020-Jan-28 at 00:29

len(list(todays_games.children)) evaluates to an integer - 5, 6, etc. You can't iterate directly over an integer with a for loop.

You can use the built-in function range to loop a set number of times if you'd need, but you should iterator directly over todays_games.children.

A big part of Python is that it simplifies iterator usage. Instead of using indices to access things like an array, (asking for the 5th element, etc) you can directly access the element with the for loop.

Source https://stackoverflow.com/questions/59940722

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

Vulnerabilities

No vulnerabilities reported

Install nba-prediction

You can download it from GitHub.
You can use nba-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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