US 12,412,103 B1
Monitoring and visualization of model-based clustering definition performance
Yanpei Chen, Sunnyvale, CA (US); and Archana Ganapathi, Palo Alto, CA (US)
Assigned to SPLUNK LLC, San Jose, CA (US)
Filed by Splunk Inc., San Francisco, CA (US)
Filed on Jan. 31, 2022, as Appl. No. 17/589,445.
Claims priority of provisional application 63/143,477, filed on Jan. 29, 2021.
Int. Cl. G06N 5/022 (2023.01); G06Q 30/0201 (2023.01)
CPC G06N 5/022 (2013.01) [G06Q 30/0201 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computing device, comprising:
one or more hardware processors; and
a non-transitory computer-readable medium having stored thereon instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising:
generating a cohort definition using a machine learning model based on a combination of a number (D) of dimensions selected from a first data set comprising first data points, wherein the cohort definition clusters the first data points into a number (K) of first clusters, each of the first clusters having a first center point;
applying the machine learning model to a second data set comprising second data points to determine a second center point for each of K of second clusters;
causing a user interface to be presented on a display device, the user interface comprising an indication of a difference measure between the first clusters and the second clusters, wherein the different measure is generated based on a difference vector determined for each second center point and a nearest first center point.