U. Harita, V. U. Kumar, Dorababu Sudarsa, G. R. Krishna, C. Z. Basha, B. S. S. P. Kumar
{"title":"A Fundamental Study on Suicides and Rainfall Datasets Using basic Machine Learning Algorithms","authors":"U. Harita, V. U. Kumar, Dorababu Sudarsa, G. R. Krishna, C. Z. Basha, B. S. S. P. Kumar","doi":"10.1109/ICECA49313.2020.9297440","DOIUrl":null,"url":null,"abstract":"Suicides in India have been registering at an alarming rate. The rainfall rate in India is unpredictable due to changes in environment. Farmers faces huge losses due to this unpredictable rains. This leads into loss of lives and results the farmers into suicide state. Relative analysis of rainfall and suicide rate will support farmers to avoid losses due to rainfall and further suicides can be avoided. Prediction of rainfall and suicide rate is achieved in India using machine learning algorithms such as Linear regression, Logistic regression, Support Vector Machine and Random Forest. Relative analysis provides better prediction results which greatly supports the farmers and avoid losses.","PeriodicalId":297285,"journal":{"name":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECA49313.2020.9297440","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Suicides in India have been registering at an alarming rate. The rainfall rate in India is unpredictable due to changes in environment. Farmers faces huge losses due to this unpredictable rains. This leads into loss of lives and results the farmers into suicide state. Relative analysis of rainfall and suicide rate will support farmers to avoid losses due to rainfall and further suicides can be avoided. Prediction of rainfall and suicide rate is achieved in India using machine learning algorithms such as Linear regression, Logistic regression, Support Vector Machine and Random Forest. Relative analysis provides better prediction results which greatly supports the farmers and avoid losses.