MACHINE LEARNING TECHNIQUES FOR HYBRID TEMPORAL-UTILITY CLASSIFICATION DETERMINATIONS

MACHINE LEARNING TECHNIQUES FOR HYBRID TEMPORAL-UTILITY CLASSIFICATION DETERMINATIONS

Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis operations by dynamically determining a hybrid temporal-utility classification for a predictive entity. The hybrid temporal...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: YADAV, Raghvendra Kumar, BHATTACHARJEE, Biswajit, NIGAM, Apoorva, WOLF, Anders, G, Vaishnavi V, KYANAM, Subhadradevi
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis operations by dynamically determining a hybrid temporal-utility classification for a predictive entity. The hybrid temporal-utility classification for the predictive entity may be determined based at least in part on outputs from a temporal score generation machine learning model and a utility score generation machine learning model.