Self-Organizing Maps for Imputation of Missing Data in Incomplete Data Matrices

The problem of incomplete data matrices is repeatedly found in large databases; posing a significant obstacle for an effective treatment of data. This paper examines a self-organizing-map (SOM) based method of data imputation under the concept of distance object per one weight; to predict physicoche...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Folguera, Laura, Zupan, Jure, Cicerone, Daniel, Magallanes, Jorge
Format: Texto completo
Sprache:Inglés
Veröffentlicht: Elsevier Science Bv 2015
Schlagworte:
CHEMOMETRICS
ARTIFICIAL NEURAL NETWORK
SELF-ORGANIZING MAPS
MISSING DATA IMPUTATION
ENVIRONMENTAL DATA SET
CIENCIAS QUÍMICAS
CIENCIAS EXACTAS Y NATURALES
Online Zugang:https://ri.unsam.edu.ar/handle/123456789/1009

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