Population modeling system based on multiple data sources having missing entries

Population modeling system based on multiple data sources having missing entries

A neural network is used to model to model the joint distribution of attributes across multiple health surveys. These multiple health surveys include large scale survey datasets and small scale survey datasets. The neural network model is trained using a combined dataset of the large scale survey da...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Mizes, Howard, Motwani, Kush, Santra, Bishal
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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Beschreibung
Zusammenfassung:A neural network is used to model to model the joint distribution of attributes across multiple health surveys. These multiple health surveys include large scale survey datasets and small scale survey datasets. The neural network model is trained using a combined dataset of the large scale survey datasets and the small scale survey datasets. The large scale survey datasets and the small scale survey datasets may include missing value indicators. The joint distribution of attributes modeled by the neural network model are the used to impute substitute values for the missing values to thereby create an output large scale dataset that does not include missing values.