AnomalyDetection.rb
Learn how it works
Installation
Add this line to your application’s Gemfile:
gem 'anomaly_detection'
Getting Started
Detect anomalies in a time series
100, Date.parse("2020-01-02") => 150, Date.parse("2020-01-03") => 136, # ... } AnomalyDetection.detect(series, period: 7) ">
series = { Date.parse("2020-01-01") => 100, Date.parse("2020-01-02") => 150, Date.parse("2020-01-03") => 136, # ... } AnomalyDetection.detect(series, period: 7)
Works great with Groupdate
series = User.group_by_day(:created_at).count
AnomalyDetection.detect(series, period: 7)
Series can also be an array without times (the index is returned)
series = [100, 150, 136, ...]
AnomalyDetection.detect(series, period: 7)
Options
Pass options
AnomalyDetection.detect(
series,
period: 7, # number of observations in a single period
alpha: 0.05, # level of statistical significance
max_anoms: 0.1, # maximum number of anomalies as percent of data
direction: "both", # pos, neg, or both
verbose: false # show progress
)
Plotting
Add Vega to your application’s Gemfile:
gem 'vega'
And use:
AnomalyDetection.plot(series, anomalies)
Credits
This library was ported from the AnomalyDetection R package and is available under the same license. It uses cdflib for the quantile function.
References
History
View the changelog
Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- Report bugs
- Fix bugs and submit pull requests
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
git clone https://github.com/ankane/AnomalyDetection.rb.git
cd AnomalyDetection.rb
bundle install
bundle exec rake compile
bundle exec rake test
