UPDATING ATTRIBUTE DATA STRUCTURES TO INDICATE JOINT RELATIONSHIPS AMONG ATTRIBUTES AND PREDICTIVE OUTPUTS FOR TRAINING AUTOMATED MODELING SYSTEMS

UPDATING ATTRIBUTE DATA STRUCTURES TO INDICATE JOINT RELATIONSHIPS AMONG ATTRIBUTES AND PREDICTIVE OUTPUTS FOR TRAINING AUTOMATED MODELING SYSTEMS

Attribute data structures can be updated to indicate joint relationships among attributes and predictive outputs in training data that can be used for training automated modeling system. A data structure that stores training data for training an automated modeling algorithm can be accessed. The trai...

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Bibliographische Detailangaben
Hauptverfasser: MIN, Xinyu, OUYANG, Jeffrey Qijia
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
HANDLING RECORD CARRIERS
PHYSICS
PRESENTATION OF DATA
RECOGNITION OF DATA
RECORD CARRIERS
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Zusammenfassung:Attribute data structures can be updated to indicate joint relationships among attributes and predictive outputs in training data that can be used for training automated modeling system. A data structure that stores training data for training an automated modeling algorithm can be accessed. The training data can include first data for a first attribute and second data for a second attribute. The data structure can be modified to include a derived attribute that indicates a joint relationship among the first attribute, the second attribute, and a predictive output variable. The automated modeling algorithm can be trained with the first attribute, the second attribute, and the derived attribute.