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Anomaly

Easy-to-use anomaly detection for Ruby

Build Status

Installation

Add this line to your application’s Gemfile:

gem 'anomaly'

Getting Started

Say we have weather data and we want to predict if it’s sunny. In this example, sunny days are non-anomalies, and days with other types of weather (rain, snow, etc.) are anomalies. The data looks like:

# [temperature(°F), humidity(%), pressure(in), sunny?(y=0, n=1)]
weather_data = [
  [85, 68, 10.4, 0],
  [88, 62, 12.1, 0],
  [86, 64, 13.6, 0],
  [88, 90, 11.1, 1],
  ...
]

The last column must be 0 for non-anomalies, 1 for anomalies. Non-anomalies are used to train the detector, and both anomalies and non-anomalies are used to find the best value of ε.

Train the detector

detector = Anomaly::Detector.new(weather_data)

Test for anomalies

# 85°F, 42% humidity, 12.3 in. pressure
detector.anomaly?([85, 42, 12.3])

Anomaly automatically finds the best value for ε, which you can access with:

detector.eps

If you already know you want ε = 0.01, initialize the detector with:

detector = Anomaly::Detector.new(weather_data, eps: 0.01)

Persistence

You can easily persist the detector to a file or database - it’s very tiny.

bin = Marshal.dump(detector)
File.binwrite("detector.bin", bin)

Then read it later:

bin = File.binread("detector.bin")
detector = Marshal.load(bin)

Related Projects

  • IsoTree - Outlier/anomaly detection for Ruby using Isolation Forest
  • OutlierTree - Explainable outlier/anomaly detection for Ruby
  • MIDAS - Edge stream anomaly detection for Ruby
  • Trend - Anomaly detection and forecasting for Ruby

Credits

A special thanks to Andrew Ng.

History

View the changelog

Contributing

Everyone is encouraged to help improve this project. Here are a few ways you can help:

To get started with development:

git clone https://github.com/ankane/anomaly.git
cd anomaly
bundle install
bundle exec rake spec

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Easy-to-use anomaly detection for Ruby

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