Prediction of Number of Suicidal People Based on KNN

被引:2
作者
Aslan, Haci Ismail [1 ]
Yilmaz, Adnan Berat [2 ]
Jeong, Namgyu [1 ]
Lee, Saebom [1 ]
Choi, Chang [1 ]
机构
[1] Gachon Univ, Dept Comp Engn, Seongnam, South Korea
[2] Hacettepe Univ, Dept Elect & Elect Engn, Ankara, Turkey
来源
2022 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC) | 2022年
基金
新加坡国家研究基金会;
关键词
visualization; suicide; prediction;
D O I
10.1109/ICEIC54506.2022.9748557
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页数:4
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