Naive Bayes Classifier for depression detection using text data

被引：1

作者：

Samanvitha, S. ^{[1
]}

Bindiya, A. R. ^{[1
]}

Sudhanva, Shreya ^{[1
]}

Mahanand, B. S. ^{[1
]}

机构：

[1] JSS Sci & Technol Univ, Dept Comp Sci & Engn, Mysuru, India

来源：

2021 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, COMMUNICATION, COMPUTER TECHNOLOGIES AND OPTIMIZATION TECHNIQUES (ICEECCOT) | 2021年

关键词：

Depression; Naive Bayes Classifier; Machine Learning;

D O I：

10.1109/ICEECCOT52851.2021.9708014

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Depression is a prevalent medical illness that affects one's emotions. Despite the large demography of people suffering from depression, It goes unnoticed more of ten than it should be. Timely detection and treatment of this illness can prevent further complications. With the outburst of social media, it has been noticed that people express their feelings on the plat form rather than seeking professional help. In this work Naive Bayes Classifier, Logistic Regression Model, Random Forest Classifier and Support Vector Machine Classifier were used for classification. The results indicated that Naive Bayes Classifier performed better when compared to other classifiers.

引用

页码：418 / 421

页数：4

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