ADAPTIVE MACHINE LEARNING THRESHOLD

ADAPTIVE MACHINE LEARNING THRESHOLD

In an example embodiment, a solution is provided wherein a threshold used by a classifier in a first machine learning model is dynamically set by a second machine learning model. More particularly, the threshold may be selected from two or more different threshold settings, based on the output of th...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Lewis, Michael, Bondoux, Alexandre Franck
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:In an example embodiment, a solution is provided wherein a threshold used by a classifier in a first machine learning model is dynamically set by a second machine learning model. More particularly, the threshold may be selected from two or more different threshold settings, based on the output of the second machine learning model. This acts to improve the reliability of predictions made by the first machine learning model in certain use cases where circumstances not adequately captured by the first machine learning model can affect the accuracy of the threshold used by the first machine learning model.