Prediction of Number of Suicidal People Based on KNN

Aslan H. I., Yilmaz A. B., Jeong N., Lee S., Choi C.

2022 International Conference on Electronics, Information, and Communication, ICEIC 2022, Jeju, South Korea, 6 - 09 February 2022 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/iceic54506.2022.9748557
  • City: Jeju
  • Country: South Korea
  • Keywords: visualization, suicide, prediction
  • Hacettepe University Affiliated: Yes


© 2022 IEEE.Population change which may be eventuated by any reason is a prominent fact for society. Both governmental and non-governmental organizations (NGOs) trying to track down the impact of community loss to understand the roots of this problem. In this study, suicide, one of the most evitable reasons for death, has been highlighted. Hereby, it was aimed to visualize the data and predict the decrease in population caused by suicide. World Health Organization's latest data and methods to visualize data and predict suicidal people have been shown in the following sub-titles in this paper. Three different interpretable algorithms were used in the study to compare their results. As a result of prediction algorithms, kNN showed an accuracy of %91.