Machine Learning Algorithms based Detection and Analysis of Stress - A Review

Now-a-days stress is one of the major issues in every individual’s life. It may cause many physiological and psychological problems. Many researchers have taken this into account and proposed various stress detection models. This paper mainly focuses on various stress detection models which are published in the latest years. The stress level of an individual is classified using machine learning algorithms like K-Nearest Neighbor (KNN), Naive Bayes (NB), Logistic regression (LR), Support Vector Machine (SVM) etc. It is observed that SVM produces a high accuracy when compared with other classifiers. The organization of the paper is as follows, Section I gives a brief introduction on stress and a basic idea about the datasets used by the researchers. Section II provides literature review. Section III contains analysis on collected literature.