US 11,669,754 B2
Data management, reduction and sampling schemes for storage device failure
Nima Elyasi, San Jose, CA (US); Vikas Sinha, Sunnyvale, CA (US); Qinling Zheng, San Jose, CA (US); and Changho Choi, San Jose, CA (US)
Assigned to Samsung Electronics Co., Ltd., Suwon-si (KR)
Filed by SAMSUNG ELECTRONICS CO., LTD., Suwon-si (KR)
Filed on May 11, 2020, as Appl. No. 16/872,194.
Claims priority of provisional application 62/981,348, filed on Feb. 25, 2020.
Prior Publication US 2021/0264298 A1, Aug. 26, 2021
Int. Cl. G06F 21/00 (2013.01); G06N 5/04 (2023.01); G06F 16/23 (2019.01); G06N 20/00 (2019.01); G06Q 10/0631 (2023.01)
CPC G06N 5/04 (2013.01) [G06F 16/2379 (2019.01); G06N 20/00 (2019.01); G06Q 10/06315 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for training a machine learning model, the method comprising:
segmenting, by a processor, a dataset from a database into one or more datasets based on time period windows;
assigning, by the processor, one or more weighted values to the one or more datasets according to the time period windows of the one or more datasets;
generating, by the processor, a training dataset from the one or more datasets, wherein an amount of data generated from the one or more datasets is based on the one or more weighted values; and
training, by the processor, the machine learning model using the training dataset.