Naïve Bayes Classifier for depression detection using text data
S. Samanvitha, A. R. Bindiya, Shreya Sudhanva, B. S. Mahanand
20212021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT)13 citationsDOI
Abstract
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 Naïve Bayes Classifier, Logistic Regression Model, Random Forest Classifier and Support Vector Machine Classifier were used for classification.TheresultsindicatedthatNaïveBayesClassifierperfor medbetterwhencomparedtootherclassifiers.
Topics & Concepts
Naive Bayes classifierLogistic regressionSupport vector machineFeelingClassifier (UML)Random forestArtificial intelligenceMachine learningComputer scienceBayes' theoremPsychologyPattern recognition (psychology)Social psychologyBayesian probabilitySentiment Analysis and Opinion MiningMental Health via WritingSpam and Phishing Detection