GithubHelp home page GithubHelp logo

docpenyu / anomalydetection Goto Github PK

View Code? Open in Web Editor NEW

This project forked from ihepcc-storage/anomalydetection

0.0 0.0 0.0 31.15 MB

anomalydetection

Python 63.11% HTML 1.66% JavaScript 34.06% CSS 0.86% Tcl 0.28% PowerShell 0.02% Batchfile 0.02%

anomalydetection's Introduction

anomalydetection_framework

异常检测框架
算法层包括预测算法和检测算法 预测算法已内置lstm/EWMA/SMA/ARIMA等 检测算法已内置Isolation Forest/N-Sigma/Q-function
框架实现了样本可视化、预测结果可视化、检测结果可视化、高位数据可视化、人工打标等功能。

anomalydetection's People

Contributors

summerchenjuan avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.