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An implementation of the Random Cut Forest data structure for sketching streaming data, with support for anomaly detection, density estimation, imputation, and more.

License: Apache License 2.0

Java 86.80% Rust 13.20%

random-cut-forest-by-aws's Introduction

Random Cut Forest by AWS

This repository contains implementations of the Random Cut Forest (RCF) probabilistic data structure. RCFs were originally developed at Amazon to use in a nonparametric anomaly detection algorithm for streaming data. Later new algorithms based on RCFs were developed for density estimation, imputation, and forecasting.

The different directories correspond to equivalent implementations in different languages, and bindings to to those base implementations, using language specific features for greater flexibility of use.

Documentation

Guha, S., Mishra, N., Roy, G., & Schrijvers, O. (2016, June). Robust random cut forest based anomaly detection on streams. In International conference on machine learning (pp. 2712-2721).

Code of Conduct

This project has adopted an Open Source Code of Conduct.

Security issue notifications

If you discover a potential security issue in this project we ask that you notify AWS/Amazon Security via our vulnerability reporting page. Please do not create a public GitHub issue.

Licensing

See the LICENSE file for our project's licensing. We will ask you to confirm the licensing of your contribution.

Copyright

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