Metadata-Version: 2.1
Name: mimizuku
Version: 0.2.30
Summary: A package for anomaly detection using Isolation Forest for Wazuh Alerts
Home-page: https://github.com/pyama86/mimizuku
Author: pyama86
Author-email: www.kazu.com@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: joblib
Requires-Dist: orjson

# Mimizuku

Mimizuku is a Python package for anomaly detection using Isolation Forest. It is designed to process log files and detect anomalies based on a variety of features.

## Installation

```bash
pip install .
```

## Usage

```python

from mimizuku import Mimizuku

# Initialize the model
model = Mimizuku(n_estimators=500)

# Train the model with a log file or DataFrame
model.fit("./training.json")

# Save the trained model
model.save_model("./model.pkl")

# Load the model and use it for prediction
loaded_model = Mimizuku.load_model("./model.pkl")
anomalies_df = loaded_model.predict("./test.json")

# Display detected anomalies
print(anomalies_df)
```
