Skip to main content

A package for anomaly detection using Isolation Forest for Wazuh Alerts

Project description

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

pip install .

Usage

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)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mimizuku-0.2.29.tar.gz (3.6 kB view hashes)

Uploaded Source

Built Distribution

mimizuku-0.2.29-py3-none-any.whl (4.3 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page