semvec/pypi-packages huggingface dataset:
iBRF 0.1.1
Improved Balanced Random Forest (iBRF) Classifier
License: MIT
Requires Python: >=3.8


# iBRF

This repository contains the code and supplementary files for the proposed iBRF (Improved Balanced Random Forest) classifier. 

## Dependencies

This project uses the following libraries:

[![scikit-learn](https://img.shields.io/badge/scikit--learn-1.3.1-orange?logo=scikit-learn)](https://scikit-learn.org/)
[![imbalanced-learn](https://img.shields.io/badge/imblearn-0.11.0-blue?logo=python)](https://imbalanced-learn.org/)



# Paper

The paper on this work has been published in IEEE Xplore.

Title - iBRF: Improved Balanced Random Forest Classifier

DOI: https://doi.org/10.23919/FRUCT61870.2024.10516372
## Synopsis

This paper proposes a modification to the original BRF classifier for enhanced prediction performance. 

In the original algorithm, the Random Undersampling (RUS) technique is utilized to balance the bootstrap samples. However, randomly eliminating too many samples from the data leads to significant data loss, resulting in a major decline in performance.

This paper proposed a novel sampling approach that, when incorporated into the framework of the RF classifier, achieves better and more generalized prediction performance. The proposed algorithm outperforms the original BRF classifier. 


Original BRF classifier implementation in the imblearn library: https://imbalanced-learn.org/stable/references/generated/imblearn.ensemble.BalancedRandomForestClassifier.html



## Installation
```bash
pip install iBRF
```

## Usage
```
from ibrf import iBRF

clf = iBRF(balance_split=0.65, n_estimators=200, random_state=42)
clf.fit(X_train, y_train)
y_pred = clf.predict(X_test)
```



## Screenshots

![App Screenshot](https://github.com/newaz-aa/iBRF/blob/main/ibrf_4.png)


## Note
This repository currently contains the earliest version of the proposed iBRF framework. A more advanced version is currently under development.


LemaÃŽtre, G., Nogueira, F. and Aridas, C.K., 2017. Imbalanced-learn: A python toolbox to tackle the curse of imbalanced datasets in machine learning. Journal of machine learning research, 18(17), pp.1-5. 

## BibTex Citation

```
@INPROCEEDINGS{10516372,
  author={Newaz, Asif and Mohosheu, Md. Salman and Noman, Md. Abdullah Al and Jabid, Taskeed},
  booktitle={2024 35th Conference of Open Innovations Association (FRUCT)}, 
  title={iBRF: Improved Balanced Random Forest Classifier}, 
  year={2024},
  volume={},
  number={},
  pages={501-508},
  keywords={Technological innovation;Data preprocessing;Benchmark testing;Prediction algorithms;Data models;Classification algorithms;Ensemble learning},
  doi={10.23919/FRUCT61870.2024.10516372}}
```
commandchat 0.0.12
use command to chat with openai models
License: MIT
Requires Python: >=3.8

[English](README.md) | [中文](README-zh.md)

# openai-commandchat 

## Quick start

Use this command line to install the python packages:

```bash
pip3 install commandchat
```
Or use the following command line to guide you to a specific python version, if you have multiple versions of python locally
```bash
python3.x -m pip3 install commandchat
```



## Features
- You can set the api_key for openai with a simple command, and you can distinguish the key for your multiple accounts with a profile (default `default` if you don't specify it): `occ configure -profile`
- You can use the command `occ chat` to chat with the chat-GPT model `gpt-3.5-turbo`.
### To be implemented
- You can use the `occ image -desc` command with chat-GPT's model to describe the image you want to generate, giving you back a link to the image.
- You can use the `occ xxx -yyy` command to chat with a specified model of chat-GPT to complete a task you specify or give you advice.
- Others not yet thought of


## Requirements

A terminal with Python and pip installed:

- Installed python environment and python version >= 3.9
- Install the openai package

## Installing

```bash
pip3 install commandchat
```

## Uninstall

```bash
pip3 uninstall commandchat
```

## Feedback or questions
- You can send an email to: ``xxx.tao.c@gmail.com`` or ``xoto@outlook.be``

## License
MIT