Metadata-Version: 2.4
Name: pyegm
Version: 0.2.2
Summary: Explosive Generative Model (EGM) classifier
Author-email: CJiangqiu <17787153839@qq.com>
License-Expression: MIT
Project-URL: Homepage, https://github.com/CJiangqiu/PyEGM
Project-URL: Documentation, https://github.com/CJiangqiu/PyEGM#readme
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.21.0
Requires-Dist: scikit-learn>=1.0.0
Requires-Dist: typing-extensions>=4.0.0; python_version < "3.8"
Requires-Dist: scipy>=1.5.0
Dynamic: license-file

# PyEGM: Explosive Generative Model for Classification

PyEGM is an explosive generative model (EGM) classifier designed for incremental learning. It generates new training points during each iteration and dynamically adjusts its generation strategy based on the input data distribution. This allows it to improve over time and make accurate predictions even as the data evolves.
## 🌟 Key Features

- **Dual Generation Modes**
  - 🎯 **Hypersphere Generation**: Creates samples on dimensional spheres
  - 🌌 **Gaussian Generation**: Produces samples through probabilistic dispersion

- **Dynamic Adaptation**
  - 🔍 Local/Global radius adjustment strategies
  - ⚖️ Automatic sample pruning with decay mechanism
  - 📈 Adaptive density-aware scaling

- **Practical Advantages**
  - 🚀 Built-in incremental learning capability
  - 🛡️ Robust to class imbalance through proportional generation
  - ⚡ Efficient neighbor search with NN indexing

## Installation
To install PyEGM, you can simply use pip:
```python
pip install pyegm
```
