REDUCING INSTANCES OF INCLUSION OF DATA ASSOCIATED WITH HINDSIGHT BIAS IN A TRAINING SET OF DATA FOR A MACHINE LEARNING SYSTEM

Instances of data associated with hindsight bias in a training set of data for a machine learning system can be reduced. A first set of data, having a first set of fields, can be received. Data in a first field can be analyzed with respect to data in a second field corresponding to an event to be pr...

Full description

Saved in:
Bibliographic Details
Main Authors McGuire, Leah, Tovbin, Matvey, Nabar, Shubha, Moore, Kevin, Bhaowal, Mayukh
Format Patent
LanguageEnglish
Published 20.02.2020
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
Online AccessGet full text

Cover

More Information
Summary:Instances of data associated with hindsight bias in a training set of data for a machine learning system can be reduced. A first set of data, having a first set of fields, can be received. Data in a first field can be analyzed with respect to data in a second field corresponding to an event to be predicted. A result can be that the data in the first field is associated with hindsight bias. A second set of data, having a second set of fields, can be produced. The second set of fields can exclude the first field. One or more features associated with the second set of data can be generated. A third set of data, having the second set of fields and fields that correspond to the one or more features, can be produced. The training set of data can be produced using the third set of data.
Bibliography:Application Number: US201916264659