US 12,112,268 B2
Counter data generation for data profiling using only true samples
Fardin Abdi Taghi Abad, Seattle, WA (US); Reza Farivar, Champaign, IL (US); Vincent Pham, Champaign (VA); Kenneth Taylor, Champaign, IL (US); Mark Watson, Sedona, AZ (US); Jeremy Goodsitt, Champaign, IL (US); Austin Walters, Savoy, IL (US); and Anh Truong, Champaign, IL (US)
Assigned to CAPITAL ONE SERVICES, LLC, Mclean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Apr. 19, 2023, as Appl. No. 18/136,830.
Application 18/136,830 is a continuation of application No. 16/686,793, filed on Nov. 18, 2019, granted, now 11,663,466.
Application 16/686,793 is a continuation of application No. 16/293,836, filed on Mar. 6, 2019, granted, now 10,552,736, issued on Feb. 4, 2020.
Prior Publication US 2023/0252291 A1, Aug. 10, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 40/10 (2020.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01)
CPC G06N 3/08 (2013.01) [G06F 40/10 (2020.01); G06N 3/045 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A non-transitory computer-accessible medium having stored thereon computer-executable instructions for generating a first dual-class dataset, wherein, when a computing hardware arrangement executes the instructions, the computing arrangement is configured to perform procedures comprising:
(a) accessing a first dataset including data points belonging to a first category of data points;
(b) accessing a second dataset including data points belonging to the first category of data points and a second category of data points;
(c) labeling each data point in the first dataset with a first label to generate a first labeled dataset, and labeling each data point in the second dataset with a second label to generate a second labeled dataset;
(d) training a classification model using the first labeled dataset and the second labeled dataset;
(e) using the classification model, classifying each data point in the second labeled dataset as belonging to one of the first category of data points or the second category of data points;
(f) for each data point in the second labeled dataset classified as belonging to the first category of data points, removing the data point from the second dataset and adding the data point to the first dataset; and
(g) generating the first dual-class dataset using the first dataset and the second dataset.