A Time Series Anomaly Detection Model for All Types of Time Series
My Journey to improve Lazy Lantern’s automated time series anomaly detection model
As an Insight Data Science Fellow, I had the opportunity to work with Lazy Lantern, a computer software company that uses machine learning to provide autonomous analytics for businesses to make data-driven decisions by better understanding user behaviors. As a consultant, I was tasked with improving the time series anomaly detection models used by Lazy Lantern. In this article, I will walk you through my journey from identifying problems and challenges to reaching an unusual, yet an actionable solution.
Background
Imagine you own a website and sell your products online. Unfortunately, for your recent product release, you made a mistake and put a ridiculously low price for your products. You are a busy person, of course, and you did not realize that there was a pricing error. Yet, when people discover this “crazy deal”, there will likely be an enormous increase in traffic on your website. If you don’t correct the error fast, you could end up with huge losses, just like Amazon’s pricing error in the 2019 Prime Day event. However, if you have a tool to monitor the number of clicks of the checkout or…
