Naive Bayes Classifier for depression detection using text data

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.