US 12,468,979 B2
Early stopping of artificial intelligence model training using control limits
Lukasz G. Cmielowski, Cracow (PL); Daniel Jakub Ryszka, Cracow (PL); Wojciech Sobala, Cracow (PL); and Gregory Bramble, Larchmont, NY (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Aug. 30, 2021, as Appl. No. 17/460,689.
Prior Publication US 2023/0061222 A1, Mar. 2, 2023
Int. Cl. G06N 20/00 (2019.01)
CPC G06N 20/00 (2019.01) 25 Claims
OG exemplary drawing
 
1. A method of training an artificial intelligence model, said method comprising an iterative training loop, wherein said iterative training loop comprises:
receiving a current set of training data, wherein said current set of training data is different from training data from previous iterations of said iterative training loop;
dividing said current set of training data into a plurality of training data subsets, each training data subset having a respective training portion and a respective validation portion;
sequentially training an artificial intelligence model with said training data subsets using said respective training portions, wherein sequentially training said artificial intelligence model includes calculating a performance metric for each training data subset of said training data subsets using said respective validation portion after training using said respective training portion;
comparing performance metrics from a previous iteration of said iterative training loop to said calculated performance metrics for said training data subsets to determine whether an improving performance condition is met; and
halting said iterative training loop responsive to determining the improving performance metric condition is met at least once within a predetermined number of previous iterations.