SENTIMENTAL ANALYSIS USING MACHINE LEARNING

Abstract

Early discovery of mental health concerns by professionals can aid in more successful diagnosis and treatment of individuals. This article explores the state of artificial intelligence (AI) in the realm of mental health and possible uses in medical treatment. Anxiety and sadness are two common mental health conditions that can be helped by machine learning approaches. They are also able to identify trends and offer practical solutions for solving the issues. Feature Selection techniques have been used to decrease the attribute data. The accuracy of several machine learning methods has been examined for both the complete set of attributes and a subset of attributes. Despite the study of a number of algorithms, more effort is still required to close the gap between AI and mental health analysis. Keywords: SVM classifier, Sentimental analysis, Machine learning.