haldersourav / anomaly-detection

Comparison of various anomaly detection algorithms using scikit-learn and visualization through Plotly Dash

Anomaly detection algorithms

A set of five anomaly detection algorithms are described as well as compared here. The purpose of this webapp is to demonstrate how Plotly-Dash can be used for data visualization as well as offer a template for other interactive visualization. The five anomaly detection algorithms are as follows:

1. Robust covariance
2. One-class Support Vector Machine (SVM)
3. One-class SVM Stochastic Gradient Descent (SGD)
4. Isolation Forest
5. Local Outlier Factor

For more details, visit this link: https://scikit-learn.org/0.20/auto_examples/plot_anomaly_comparison.html