From Twitter to Swift: Constructing Anomaly Detection.
Twitter (now X), again in 2015 made an Anomaly Detection Algorithm to be used in monitoring developments amongst their hundreds of thousands of customers.
This bundle, made totally in R, continues to be very usable. It was designed to have the ability to detect international and native anomalies, and it is ready to efficiently detect all kinds of anomalies. For a whole checklist of what it might probably and may’t detect please take a look at Anomaly.io’s take a look at of the unique algorithm, as it is extremely complete.
Why not 🤷♂️? I used to be bored.
Twitter’s Anomaly Detection Algorithm is a statistical framework designed for detecting anomalies, or outliers, in a time-series dataset.
There are two most important core elements to the algorithm.
- Seasonal Decomposition: The algorithm…
