Metadata-Version: 2.4
Name: SFDL_DB
Version: 0.1.0
Summary: Same Features, Different Label Skew Generator
Home-page: https://github.com/yourusername/SFDL_DB
Author: Your Name
Author-email: Your Name <your.email@example.com>
License: MIT
Project-URL: Homepage, https://github.com/yourusername/SFDL_DB
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: scikit-learn
Dynamic: author
Dynamic: home-page

# SFDL_DB

A Python package for generating Same Features, Different Label Skew datasets using KMeans clustering and Davies-Bouldin Score for optimal `k`.

## Installation

```bash
pip install .
```

## Usage

```python
from SFDL_DB import same_features_different_label_skew
import pandas as pd

df = pd.read_csv("your_dataset.csv")
same_features_different_label_skew(df, label_col="Attack", k_optimal=4)
```
