isolation-forest

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

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

⭐ An anomaly-based intrusion detection system.

implement the machine learning algorithms by python for studying

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

Security Analytics Engine - Anomaly Detection in Web Traffic

Detect suspicious financial transactions using SQL and Python. Build user-level behavioral features in SQLite, apply Isolation Forest for anomaly detection, and visualize high-risk patterns. Demonstrates unsupervised fraud analytics and SQL-driven data science workflow.

Anomaly detection in synthetic transaction and sales data with Python. Generates realistic data, injects unusual events, and applies Isolation Forest, Local Outlier Factor, and Z-score methods to detect outliers. Produces anomaly reports and visualizations for portfolio-ready demonstration of data science skills.

Simple machine learning tool in Python (>=3.7) computing an anomaly score of seismic waveform amplitudes. By using a pre-trained Isolation forest model, the program can be used for identification of outliers in semismic data, assign robustness weights, or check instruments and metadata errors

Combination Robust Cut Forests: Merging Isolation Forests and Robust Random Cut Forests

🚀 Financial Anomaly Detection with DeepSeek and Isolation Forest – A powerful, locally-run tool for detecting financial anomalies using Isolation Forest and DeepSeek LLM. Features AI-powered insights, interactive time-series visualization, and automated PDF audit reports. 🔍📊

Anomaly detection using isolation forest

The code for Isolation Mondrian (iMondrian) forest for batch and online anomaly detection

BMW MHD log anomaly detector — a damn useful tool for tuners and enthusiasts. Detects log anomalies using Isolation Forests trained on real driving data with binary features for AFR spikes, throttle faults, and RPM anomalies.

Secure Federated Learning system with Byzantine attack detection, trust scoring, and real-time SOC dashboard. Built with Flower (flwr), PyTorch, FastAPI, and Next.js. Final Year Project — Bahria University 2026.

This project builds an interactive Streamlit dashboard for customer segmentation using KMeans clustering and anomaly detection using Isolation Forest.

Real-time anomaly detection system for GitHub activity using Airflow, MLflow, and Terraform

An implementation of isolation forest algorithm to detect anomalies

Implementing and improving the State-Of-The-Art (non-DL based) Anomaly Detection algorithms.

Preprocessing and Analyzing NYC Yellow taxi passenger count for 2022 and 2023 using Isolation forest