Isolation Forest on Spark

UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.

A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.

(Python, R, C/C++) Isolation Forest and variations such as SCiForest and EIF, with some additions (outlier detection + similarity + NA imputation)

This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

implement the machine learning algorithms by python for studying

offical implementation of TKDE paper "Deep isolation forest for anomaly detection"

C++, rust, julia, python2, and python3 implementations of the Isolation Forest anomaly detection algorithm.

⭐ An anomaly-based intrusion detection system.

This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets

Implementation of feature engineering from Feature engineering strategies for credit card fraud

Official repository of the paper "Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance", M. Carletti, M. Terzi, G. A. Susto.

Surface water quality data analysis and prediction of Potomac River, West Virginia, USA. Using time series forecasting, and anomaly detection : ARIMA, SARIMA, Isolation Forest, OCSVM and Gaussian Distribution

Isolation forest implementation in Go

Using Unsupervised methods to identify anomalies in user behaviour through IP Profiling

Package implements decision tree and isolation forest

Anomaly detection using isolation forest

Security Analytics Engine - Anomaly Detection in Web Traffic

Machine learning algorithm to detect fraudulent credit card transactions

An implementation of isolation forest algorithm to detect anomalies