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.
Ignoring an upcoming (known) window of time
Two methods can be used to ignore an upcoming window of...
