US 11,892,932 B2
Interface for visualizing and improving model performance
Arijit Sengupta, San Francisco, CA (US); Jonathan Wray, San Francisco, CA (US); Grigory Nudelman, San Francisco, CA (US); Daniel Kane, San Francisco, CA (US); and Geoffrey Grant, San Francisco, CA (US)
Assigned to AIBLE INC., Pleasanton, CA (US)
Filed by Aible Inc., Pleasanton, CA (US)
Filed on Jul. 13, 2022, as Appl. No. 17/812,246.
Application 17/812,246 is a continuation of application No. 16/230,655, filed on Dec. 21, 2018, granted, now 11,429,508.
Application 16/230,655 is a continuation of application No. 16/169,208, filed on Oct. 24, 2018, granted, now 10,586,164, issued on Mar. 10, 2020.
Claims priority of provisional application 62/745,966, filed on Oct. 15, 2018.
Prior Publication US 2022/0342793 A1, Oct. 27, 2022
Int. Cl. G06F 11/00 (2006.01); G06F 11/34 (2006.01); G06N 3/08 (2023.01); G06T 11/20 (2006.01); G06F 16/901 (2019.01); G06N 20/00 (2019.01); G06N 7/01 (2023.01)
CPC G06F 11/3447 (2013.01) [G06F 16/9024 (2019.01); G06N 3/08 (2013.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06T 11/206 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving data characterizing performance of a generated model, wherein the received data is based on monitoring performance of the generated model while the generated model is being used for classification on live data;
determining a first performance value of the generated model based on the received data characterizing performance of the generated model;
rendering, within a graphical user interface, a plot including a first axis and a second axis, the first axis including a characterization of a first performance metric and the second axis including a characterization of a second performance metric; and
rendering, within the graphical user interface and the plot, a first graphical object at a first location characterizing the first performance value, the first graphical object providing a visual representation of the characteristics of the generated model and/or requirements of the generated model.