Metadata-Version: 2.1
Name: quick-anomaly-detector
Version: 0.2.18
Summary: models class for quick Anomaly Detection
Home-page: https://github.com/cheerzhang/AnomalyDetectionModel
Author: ZhangLe
Author-email: zhangle@gmail.com
Project-URL: Bug Tracker, https://github.com/cheerzhang/AnomalyDetectionModel/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.11.2
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=0.25.1
Requires-Dist: numpy>=1.21.5
Requires-Dist: plotly>=5.18.0
Requires-Dist: matplotlib>=3.7.1
Requires-Dist: SciPy>=1.11.4
Requires-Dist: cdifflib>=1.2.6
Requires-Dist: torch>=2.2.0
Requires-Dist: scikit-learn>=1.4.0
Requires-Dist: xgboost>=2.0.3
Requires-Dist: mlflow>=2.10.2

# AnomalyDetectionModel
AnomalyDetectionModels

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

## Overview

`AnomalyDetectionModel` is a python library that includs some simple implementation of an anomaly detection model.   
For more details, please refer to the document page:   
[Document](https://anomalydetectionmodel.readthedocs.io/en/latest/index.html)   
pypi page link is here:(https://pypi.org/project/quick-anomaly-detector/)   

### Quick Start
#### Installation

You can install `Anomaly Detection Model` using pip:

```
pip install quick-anomaly-detector
```

Quick Start:   
```
from quick_anomaly_detector.models import AnomalyGaussianModel


# Load your datasets (X_train, X_val, y_val)
model = AnomalyGaussianModel()

# Train the model
model.train(X_train, X_val, y_val)

# Predict anomalies in the validation dataset
anomalies = model.predict(X_val)

```
