Simulation of suicide tendency by using machine learning

Hugo David Calderon Vilca, William I. Wun-Rafael, Roberto Miranda-Loarte

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Suicide is one of the most distinguished causes of death on the news worldwide. There are several factors and variables that can lead a person to commit this act, for example, stress, self-esteem, depression, among others. The causes and profiles of suicide cases are not revealed in detail by the competent institutions. We propose a simulation with a systematically generated dataset; such data reflect the adolescent population with suicidal tendency in Peru. We will evaluate three algorithms of supervised machine learning as a result of the algorithm C4.5 which is based on the trees to classify in a better way the suicidal tendency of adolescents. We finally propose a desktop tool that determines the suicidal tendency level of the adolescent.

Original languageEnglish
Title of host publication2017 36th International Conference of the Chilean Computer Science Society, SCCC 2017
PublisherIEEE Computer Society
Pages1-6
Number of pages6
ISBN (Electronic)9781538634837
DOIs
StatePublished - 5 Jul 2018
Externally publishedYes
Event36th International Conference of the Chilean Computer Science Society, SCCC 2017 - Arica, Chile
Duration: 16 Oct 201720 Oct 2017

Publication series

NameProceedings - International Conference of the Chilean Computer Science Society, SCCC
Volume2017-October
ISSN (Print)1522-4902

Conference

Conference36th International Conference of the Chilean Computer Science Society, SCCC 2017
Country/TerritoryChile
CityArica
Period16/10/1720/10/17

Keywords

  • classification
  • machine learning
  • prevention
  • suicide
  • suicide attempt
  • suicide risk
  • Suicide tendency

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