US 12,412,127 B2
Data clean-up method for improving predictive model training
Akli Adjaoute, Mill Valley, CA (US)
Assigned to Brighterion, Inc., Purchase, NY (US)
Filed by Brighterion, Inc., Purchase, NY (US)
Filed on Aug. 22, 2023, as Appl. No. 18/453,914.
Application 18/453,914 is a continuation of application No. 17/085,109, filed on Oct. 30, 2020, granted, now 11,734,607, issued on Aug. 22, 2023.
Application 17/085,109 is a continuation of application No. 16/398,917, filed on Apr. 30, 2019, granted, now 10,846,623, issued on Nov. 24, 2020.
Application 16/398,917 is a continuation of application No. 14/935,742, filed on Nov. 9, 2015, abandoned.
Application 14/935,742 is a continuation in part of application No. 14/815,934, filed on Jul. 31, 2015, abandoned.
Application 14/815,934 is a continuation in part of application No. 14/815,848, filed on Jul. 31, 2015, abandoned.
Application 14/815,848 is a continuation in part of application No. 14/514,381, filed on Oct. 15, 2014, abandoned.
Application 14/935,742 is a continuation in part of application No. 14/521,667, filed on Oct. 23, 2014, abandoned.
Prior Publication US 2024/0046156 A1, Feb. 8, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 20/00 (2019.01); G06F 16/215 (2019.01); G06N 5/04 (2023.01)
CPC G06N 20/00 (2019.01) [G06F 16/215 (2019.01); G06N 5/04 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method for training a predictive model, the method comprising, via one or more transceivers and/or processors:
receiving a plurality of records, each of the plurality of records including a plurality of data fields and the predictive model including a smart agent corresponding to each of the plurality of data fields and a classification model including one or more of data mining logic, a neural network, case-based-reasoning, clustering or business rules;
generating a record file including a value populating each of the plurality of data fields;
executing a computer learning training algorithm to train the plurality of smart agents and the one or more classification models of the predictive model based on the record file including by—
for each of plurality of data fields that is numeric, determining at least one normal numeric value interval based on the plurality of values in the record file populating the corresponding one of the plurality of data fields,
for each of the plurality of data fields that is symbolic, determining at least one normal symbolic value based on the plurality of values in the record file populating the corresponding one of the plurality of data fields,
wherein the predictive model is configured to combine a plurality of scores output by the plurality of smart agents and the one or more classification models into a single result.