Ignoring time periods
Often, people ask how they can get ML to ignore the fact that a certain event has occurred. Perhaps it was an expected maintenance window, or perhaps something was broken within the data ingest pipeline and data was lost for a few moments. There are a few ways that you can get ML to ignore time periods, and for distinction, we'll separate them into two groups:
- A known, upcoming window of time
- An unexpected window of time that is discovered only after the fact
To illustrate things, we'll use a single-metric count job (from Figure A.1) on the farequote dataset that has an anomaly on the date of February 9th:
Figure A.10 – An analysis on the farequote dataset with an anomaly we'd like to ignore
Now, let's explore the ways we can ignore the anomaly on February 9th using different situations.
