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...
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| creator | YADAV, Raghvendra Kumar BHATTACHARJEE, Biswajit NIGAM, Apoorva WOLF, Anders G, Vaishnavi V KYANAM, Subhadradevi |
| description | 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. |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING PHYSICS |
| title | MACHINE LEARNING TECHNIQUES FOR HYBRID TEMPORAL-UTILITY CLASSIFICATION DETERMINATIONS |
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