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Predicting the Depression Level of Excessive Use of Mobile Phone

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dc.contributor.author Salehin, Imrus
dc.contributor.author Talha, Iftakhar Mohammad
dc.date.accessioned 2022-02-13T03:53:05Z
dc.date.available 2022-02-13T03:53:05Z
dc.date.issued 2021-05-31
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7106
dc.description.abstract In this research titled “Predicting the Depression Level of Excessive Use of Mobile Phone: Using Machine Learning Algorithm” which is applied advanced machine learning and regression analysis to find out the depression level. We have done the whole work in the research area of medical science and information technology and also built up a collaboration. In this study, we are focusing on the strength of the algorithm and also calculate the accuracy with python programming. The result expresses that smart mobile device changing the human brain day by day if spend more time around 8 to 12 hours a day. At last, we observed that a man or woman slowly going through a depression for the impact of the excessive mobile operates. In our study, we have used multiple classification algorithms to find out depression level such as Probability, Decision Tree, Random Forest, Linear Regression and SVM (Support Vector Machine). For the accuracy of our work, we have used four types of algorithms to find the optimal ratio and percentage. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Mobile phone en_US
dc.subject Prediction algorithm en_US
dc.subject Machine learning en_US
dc.title Predicting the Depression Level of Excessive Use of Mobile Phone en_US
dc.title.alternative Using Machine Learning Algorithm en_US
dc.type Article en_US


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