Metadata-Version: 2.4
Name: imbbag
Version: 1.3
Summary: Package contains a collection of bagging ensemble algorithms for imbalanced data classification
Home-page: https://github.com/yousefabdi/imbbag
Author: Yousef Abdi
Author-email: yousef.abdi@gmail.com
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.11
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: scikit-learn
Requires-Dist: patch_sklearn
Requires-Dist: imblearn
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: PyGAD
Requires-Dist: mlxtend
Requires-Dist: scikit-learn-intelex
Requires-Dist: ARFS
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: summary

# ImbBag

## Description

ImbBag is a specialized package that integrates a variety of bagging ensemble methods specifically designed for imbalanced data classification. This package provides a scikit-learn-based framework that simplifies the usage of these methods, making it easier for researchers and practitioners to apply them in their work, whether dealing with binary or multi-class classification problems.

## Installation

```bash
pip install imbbag
```


## Requirements

The following Python packages are required.

* scikit-learn
* imblearn >= 1.2
* PyGAD == 3.0
* ARFS>2.2
* mlxtend
* patch_sklearn
* scikit-learn-intelex

Also, use Python 3.11


## Available Bagging Ensemble Algorithms in the ImbBag Package

* UnderBagging (UnderBag)
  * Multi-class
* Exactly Balanced Bagging (EBBag)
  * Binary-class
* OverBagging (OverBag)
  * Multi-class
* SMOTE Bagging (SMOTEBag)
  * Multi-class
* Roughly Balanced Bagging  (RBBag)
  * Binary-class
* Multi-class Roughly Balanced Bagging (MRBBag)
  * Multi-class
* Bagging Ensemble Variation (BEV)
  * Binary-class
* Lazy Bagging (LazyBag)
  * Multi-class
* Multi Random Balance Bagging (MultiRandBalBag)
  * Multi-class
* Neighborhood Balanced Bagging (NBBag)
  * Binary-class
* Probability Threshold Bagging (PTBag)
  * Multi-class
* Adaptive Synthetic Bagging (ADASYNBag)
  * Binary-class
* RSYN Bagging (RSYNBag)
  * Binary-class
* Resampling Ensemble Algorithm (REABag)
  * Multi-class
* Under-bagging K-NN (UnderBagKNN)
  * Multi-class
* Boundary Bagging (BBag)
  * Multi-class
* Bagging of Extrapolation-SMOTE SVM (BEBS)
  * Binary-class
* Evolutionary Under-sampling based Bagging (EUSBag)
  * Binary-class
* Random Balanced Sampling with Bagging (RBSBag)
  * Multi-class
* Cost-sensitive Bagging (CostBag)
  * Multi-class
  
  
  ## Credits

- ** Yousef Abdi 
- *University of Tabriz*
  
  
  ## License

This project licensed under the MIT License.


  ## Support

Report issues, ask questions, and provide suggestions using:

* [GitHub Issues](https://github.com/yousefabdi/ImbBag/issues)
* [GitHub Discussions](https://github.com/yousefabdi/ImbBag/discussions)
* Email: y.abdi [at] tabrizu [dot] ac [dot] ir

The project can be accessed at https://github.com/yousefabdi/imbbag
