SCUT sampling and classification algorithms to identify levels of child malnutrition

Juan Baraybar-Huambo, Juan Gutiérrez-Cárdenas

Research output: Chapter in Book/Report/Conference proceedingPaper (Conference contribution)peer-review

1 Scopus citations


Child malnutrition results in millions of deaths every year. This condition is a potential problem in Peruvian society, especially in the rural parts of the country. The consequences of malnutrition range from physical limitations to declining mental performance and productivity for the individual. Government initiatives contribute to decreasing the causes of this disorder; however, these efforts are focused on long term solutions. The need for a fast and reliable way to detect these cases early on still exists. This paper compares classification techniques to determine which one is the most appropriate to classify cases of malnutrition. Neural networks and decision trees are used in combination with different sampling techniques, such as SCUT, SMOTE, random oversampling, random undersampling, and Tomek links. The models produced using oversampling techniques achieved high accuracies. Further, the models produced by the SCUT algorithm achieved high accuracies, preserved the behavior of the data and allowed for better representations of minority classes. The multilayer perceptron model that used the SCUT sampling techniques was chosen as the best model.
Original languageEnglish
Title of host publicationInformation Management and Big Data - 6th International Conference, SIMBig 2019, Proceedings
EditorsJuan Antonio Lossio-Ventura, Nelly Condori-Fernandez, Jorge Carlos Valverde-Rebaza
Number of pages13
ISBN (Print)9783030461393
StatePublished - 1 Jan 2020
Event6th International Conference on Information Management and Big Data, SIMBig 2019 - Lima, Peru
Duration: 21 Aug 201923 Aug 2019

Publication series

NameCommunications in Computer and Information Science
Volume1070 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference6th International Conference on Information Management and Big Data, SIMBig 2019


  • Child malnutrition
  • Decision trees
  • Neural networks
  • Random forest
  • Sampling techniques


  • Conference Object

OECD Category

  • Ingeniería de sistemas y comunicaciones

Ulima Repository Category

  • Ingeniería de sistemas / Diseño y métodos

Ulima Repository Subject

  • Desnutrición en niños
  • Malnutrition in children
  • Muestreo (Estadística)
  • Neural networks (Computer science)
  • Redes neuronales (Informática)
  • Sampling (Statistics)


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