Adaptive, Hybrid Feature Selection
Python implementation of the Adaptive, Hybrid Feature Selection algorithm (AHFS), originally developed by Viharos et al. For scientific or related inquiries, please contact Dr. Zsolt János Viharos and Anh Tuan Hoang.
Getting started
Requirements
- Windows or Linux-based platform
- Python version 3.11 or better
- Optional: CUDA 11.8 or better
Installation
Install from PyPI via pip install ahfs. It is recommended that you create a separate environment.
Usage
You may run one of the preset configurations or run an instance with your own dataset and settings.
Presets
To run a preset configuration, first download the datasets folder from this repository into your working directory.
Secondly, import the desired configuration from utils.presets or use the example code found in utils.example.
Run the configuration by invoking the run() method on the class instance.
Consult the API documentation for further details.
Running your own instance
Consult the API documentation for further details.
FAQ
- I get the warning message CUDA is not available! Using CPU..
- Re-install the torch package by following these instructions.
2 maintainers
Metadata
2 maintainers
Release files for ahfs 2025.8
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Source distribution (sdist)
| File | Size | Uploaded | |
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| ahfs-2025.8.tar.gz | 44.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ahfs-2025.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 106.5 kB
Release files / ahfs-2025.8.tar.gz
| Download URL | ahfs-2025.8.tar.gz |
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| Size | 44.4 kB |
| Tags | Source |
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| Size | 62.2 kB |
| Tags | Python 3 |
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