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Attribute-Associated Neuron Modeling and Missing Value Imputation for Incomplete Data
2021
Wireless Communications and Mobile Computing
The imputation of missing values is an important research content in incomplete data analysis. Based on the auto associative neural network (AANN), this paper conducts regression modeling for incomplete data and imputes missing values. Since the AANN can estimate missing values in multiple missingness patterns efficiently, we introduce incomplete records into the modeling process and propose an attribute cross fitting model (ACFM) based on AANN. ACFM reconstructs the path of data transmission
doi:10.1155/2021/5589872
fatcat:lnbvmsac5nfc3oceubbkbgcy4u