lbfs | original lbfs | Genomics library

by fd0 C++ Version: Current License: No License

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

kandi X-RAY | lbfs Summary

lbfs is a C++ library typically used in Artificial Intelligence, Genomics applications. lbfs has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Mirror of the original lbfs (Low Bandwidth File System) cvs repository at http://www.fs.net/cvs/lbfs/ (404)

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Quality

Security

License

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Support

lbfs has a low active ecosystem.

It has 21 star(s) with 12 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

lbfs has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of lbfs is current.

Quality

lbfs has 0 bugs and 0 code smells.

Security

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

lbfs code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

lbfs 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

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

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lbfs Key Features

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lbfs Examples and Code Snippets

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Community Discussions

Trending Discussions on lbfs

How to build a pipeline finding the best preprocessing per column in a fine-grained fashion?

QUESTION

How to build a pipeline finding the best preprocessing per column in a fine-grained fashion?

Asked 2021-Dec-02 at 09:27

In sklearn we can use the column transformer within a pipeline to apply a preprocessing choice to specific columns like this:

...

ANSWER

Answered 2021-Dec-02 at 09:27

The naming convention in a pipeline is using double underscore __ to separate steps, and their parameters.

You can see the different parameter of your pipeline and their value using pipeline.get_params().

In your case the parameter preprocessing1__standardscaler is referencing the scaling preprocessing defined for the first step of your pipeline and this is the argument that should be set during the GridSearchCV.

The example below illustrates how to perform this operation:

Source https://stackoverflow.com/questions/70196163

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

Vulnerabilities

No vulnerabilities reported

Install lbfs

You can download it from GitHub.

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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