Class-Imbalance | class imbalance problem in machine learning | Machine Learning library

by VVVENIIDIICI Python Version: Current License: No License

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kandi X-RAY | Class-Imbalance Summary

Class-Imbalance is a Python library typically used in Financial Services, Banks, Payments, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Numpy, Pandas applications. Class-Imbalance has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Dealing with class imbalance problem in machine learning. Synthetic oversampling(SMOTE, ADASYN).

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Class-Imbalance has a low active ecosystem.

It has 22 star(s) with 7 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

Class-Imbalance has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Class-Imbalance is current.

Quality

Class-Imbalance has 0 bugs and 0 code smells.

Security

Class-Imbalance has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Class-Imbalance code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Class-Imbalance 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.

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

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

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Class-Imbalance Key Features

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Class-Imbalance Examples and Code Snippets

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Community Discussions

Trending Discussions on Class-Imbalance

Over and under sample multi-class training examples (rows) in a pandas dataframe to specified values

QUESTION

Over and under sample multi-class training examples (rows) in a pandas dataframe to specified values

Asked 2021-Jul-16 at 17:51

I would like to make a multi-class pandas dataframe more balanced for training. A simplified version of my training set looks as follows:

Imbalanced dataframe: counts for class 0, 1 and 2 are respectively 7, 3 and 1

...

ANSWER

Answered 2021-Jul-16 at 17:51

Since groupby.sample does not allow n to be larger than the group size if replace is not True but having replace be True means that replacement will occur even in groups that could have been downsampled.

Instead let's try with groupby.apply + sample and conditionally enable replace per group. Create a dictionary that maps each class to number of samples, and use the conditional logic to determine with or without replacement:

Source https://stackoverflow.com/questions/68413104

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

Vulnerabilities

No vulnerabilities reported

Install Class-Imbalance

You can download it from GitHub.
You can use Class-Imbalance 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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