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https://github.com/ankane/anomaly
Easy-to-use anomaly detection for Ruby
https://github.com/ankane/anomaly
Last synced: 5 days ago
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Easy-to-use anomaly detection for Ruby
- Host: GitHub
- URL: https://github.com/ankane/anomaly
- Owner: ankane
- License: mit
- Created: 2011-12-11T22:27:48.000Z (almost 13 years ago)
- Default Branch: master
- Last Pushed: 2024-10-27T18:03:58.000Z (7 days ago)
- Last Synced: 2024-10-27T21:45:03.622Z (7 days ago)
- Language: Ruby
- Homepage:
- Size: 59.6 KB
- Stars: 102
- Watchers: 8
- Forks: 5
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.txt
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README
# Anomaly
Easy-to-use anomaly detection for Ruby
[](https://github.com/ankane/anomaly/actions)
## Installation
Add this line to your application’s Gemfile:
```ruby
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:
```ruby
# [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
```ruby
detector = Anomaly::Detector.new(weather_data)
```
Test for anomalies
```ruby
# 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:
```ruby
detector.eps
```
If you already know you want ε = 0.01, initialize the detector with:
```ruby
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.
```ruby
bin = Marshal.dump(detector)
File.binwrite("detector.bin", bin)
```
Then read it later:
```ruby
bin = File.binread("detector.bin")
detector = Marshal.load(bin)
```
## Related Projects
- [AnomalyDetection.rb](https://github.com/ankane/AnomalyDetection.rb) - Time series anomaly detection for Ruby
- [Prophet.rb](https://github.com/ankane/prophet-ruby) - Time series forecasting (and anomaly detection) for Ruby
- [IsoTree](https://github.com/ankane/isotree-ruby) - Outlier/anomaly detection for Ruby using Isolation Forest
- [OutlierTree](https://github.com/ankane/outliertree-ruby) - Explainable outlier/anomaly detection for Ruby
- [MIDAS](https://github.com/ankane/midas-ruby) - Edge stream anomaly detection for Ruby
- [Random Cut Forest](https://github.com/ankane/random-cut-forest-ruby) - Random Cut Forest anomaly detection for Ruby
- [Trend](https://github.com/ankane/trend-ruby) - Anomaly detection and forecasting for Ruby
## Credits
A special thanks to [Andrew Ng](https://www.coursera.org/learn/machine-learning).
## History
View the [changelog](https://github.com/ankane/anomaly/blob/master/CHANGELOG.md)
## Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- [Report bugs](https://github.com/ankane/anomaly/issues)
- Fix bugs and [submit pull requests](https://github.com/ankane/anomaly/pulls)
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
```sh
git clone https://github.com/ankane/anomaly.git
cd anomaly
bundle install
bundle exec rake spec
```